Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection, 29. SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation, 27. In addition to ICDAR papers and their code, it would be helpful to have CVPR papers along with their code as well. Mesh Saliency: An Independent Perceptual Measure or a Derivative of Image Saliency? Interpolation-Based Semi-Supervised Learning for Object Detection, 44. Hamed Pirsiavash on LinkedIn: Our CVPR 2020 paper on detecting backdoor CVPR 2021 Workshops. Let us know if more papers can be added to this table. Hallucination Improves Few-Shot Object Detection, 32. Line Segment Detection Using Transformers without Edges, 25. Exploit Visual Dependency Relations for Semantic Segmentation, 35. Anti-Aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation, 31. Black, Zitong Yu, Chenxu Zhao, Zezheng Wang, Yunxiao Qin, Zhuo Su, Xiaobai Li, Feng Zhou, Guoying Zhao, Zhuoqian Yang, Wentao Zhu, Wayne Wu, Chen Qian, Qiang Zhou, Bolei Zhou, Chen Change Loy, Hyeongmin Lee, Taeoh Kim, Tae-young Chung, Daehyun Pak, Yuseok Ban, Sangyoun Lee, Maxim Maximov, Ismail Elezi, Laura Leal-Taixe, Zhen Zhu, Zhiliang Xu, Ansheng You, Xiang Bai, Cheng-Han Lee, Ziwei Liu, Lingyun Wu, Ping Luo, Wen Jiang, Nikos Kolotouros, Georgios Pavlakos, Xiaowei Zhou, Kostas Daniilidis, Chen Gao, Yunpeng Chen, Si Liu, Zhenxiong Tan, Shuicheng Yan, Jiashun Wang, Chao Wen, Yanwei Fu, Haitao Lin, Tianyun Zou, Xiangyang Xue, Yinda Zhang, Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao, Peidong Liu, Zhaopeng Cui, Viktor Larsson, Marc Pollefeys, Jianzhu Guo, Xiangyu Zhu, Chenxu Zhao, Dong Cao, Zhen Lei, Stan Z. Li, Yan Zhang, Mohamed Hassan, Heiko Neumann, Michael J. Capturing Omni-Range Context for Omnidirectional Segmentation, 6. Open-Vocabulary Object Detection Using Captions, Paper(Oral): https://openaccess.thecvf.com/content/CVPR2021/html/Zareian_Open-Vocabulary_Object_Detection_Using_Captions_CVPR_2021_paper.html, Code: https://github.com/alirezazareian/ovr-cnn, 53. (Face) 7. " : - - " BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation, 14. PLOP: Learning without Forgetting for Continual Semantic Segmentation, 37. Coreference Resolution Multiple-choice +5. Lesion-Aware Transformers for Diabetic Retinopathy Grading, 30. The repository contains code for CVPR 2023 submission paper titled "Selective Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching" - GitHub - AAAnonymousSubmission/RVSEPP: The repository contains code for CVPR 2023 submission paper titled "Selective Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching" Railroad Is Not a Train: Saliency As Pseudo-Pixel Supervision for Weakly Supervised Semantic Segmentation, 10. The latest in Machine Learning | Papers With Code I^3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors, 48. General Multi-Label Image Classification With Transformers, 38. addDatasetIthaca365: Dataset and Driving Perception under Repeated , add CVPR 2020Weakly Supervised Semantic Point Cloud Segmentat, addWSOLWeakly Supervised Object Localization as Domain Adaption, (Referring Video Object Segmentation), (Weakly Supervised Object Localization), (Hyperspectral Image Reconstruction), https://drive.google.com/file/d/15JFhfPboKdUcIH9LdbCMUFmGq_JhaxhC/view, https://github.com/amusi/daily-paper-computer-vision, https://github.com/facebookresearch/ConvNeXt, https://mp.weixin.qq.com/s/Xg5wPYExnvTqRo6s5-2cAw, https://github.com/megvii-research/RepLKNet, https://github.com/DingXiaoH/RepLKNet-pytorch, https://mp.weixin.qq.com/s/_qXyIQut-JRW6VvsjaQlFg, https://mp.weixin.qq.com/s/Q9-crEOz5IYzZaNoq8oXfg, https://mp.weixin.qq.com/s/yo5KmB2Y7t2R4jiOKI87HQ, https://github.com/OliverRensu/Shunted-Transformer, https://github.com/ZrrSkywalker/PointCLIP, https://github.com/omriav/blended-diffusion, https://semanticstylegan.github.io/videos/demo.mp4, https://github.com/sapphire497/style-transformer, https://www.mmlab-ntu.com/project/gpunit/, https://github.com/williamyang1991/GP-UNIT, https://github.com/RenYurui/Neural-Texture-Extraction-Distribution, https://wanyu-lin.github.io/assets/publications/wanyu-cvpr2022.pdf, https://github.com/WanyuGroup/CVPR2022-OrphicX, https://github.com/Sunshine-Ye/Beta-DARTS, https://github.com/mxin262/SwinTextSpotter, https://xharlie.github.io/projects/project_sites/pointnerf/, https://www.youtube.com/watch?v=JtBS4KBcKVc, https://grail.cs.washington.edu/projects/humannerf/, https://github.com/lulutang0608/Point-BERT, https://mp.weixin.qq.com/s/xdMfZ_L628Ru1d1iaMny0w, https://mp.weixin.qq.com/s/MkQT8QWSYoYVhJ1RSF6oPQ, https://github.com/amazon-research/omni-detr, https://github.com/SvipRepetitionCounting/TransRAC, https://github.com/zengwang430521/TCFormer, https://github.com/POSTECH-CVLab/FastPointTransformer, https://github.com/dvlab-research/Stratified-Transformer, https://github.com/xyupeng/ContrastiveCrop, https://mp.weixin.qq.com/s/VTP9D5f7KG9vg30U9kVI2A, https://mp.weixin.qq.com/s/jkYR8mYp-e645qk8kfPNKQ, https://github.com/DensoITLab/TeachAugment, https://github.com/shashankvkt/AlignMixup_CVPR22, https://github.com/megvii-research/mdistiller, https://mp.weixin.qq.com/s/-4AA0zKIXh9Ei9-vc5jOhw, https://mp.weixin.qq.com/s/UnUJJBwcAsRgz6TnQf_b7w, https://mp.weixin.qq.com/s/dxss8RjJH283h6IbPCT9vg, https://mp.weixin.qq.com/s/yDkreTudC8JL2V2ETsADwQ, https://github.com/vision4robotics/TCTrack, https://zhang-pengyu.github.io/DUT-VTUAV/, http://cvlab.postech.ac.kr/research/FIFO/, https://mp.weixin.qq.com/s/knSnlebdtEnmrkChGM_0CA, https://mp.weixin.qq.com/s/-08olqE7np8A1XQzt6HAgQ, https://jiaya.me/papers/cvpr22_zhuotao.pdf, https://github.com/dvlab-research/GFS-Seg, https://sites.google.com/view/generic-grouping/, https://github.com/facebookresearch/Generic-Grouping, https://jialianwu.com/projects/EfficientVIS.html, https://github.com/zhiqi-li/Panoptic-SegFormer, https://github.com/VIPSeg-Dataset/VIPSeg-Dataset/blob/main/VIPSeg2022.pdf, https://github.com/VIPSeg-Dataset/VIPSeg-Dataset, https://mp.weixin.qq.com/s/8t12Y34eMNwvJr8PeryWXg, https://github.com/ckkelvinchan/BasicVSR_PlusPlus, https://mp.weixin.qq.com/s/HZTwYfphixyLHxlbCAxx4g, https://github.com/MohamedAfham/CrossPoint, https://www.youtube.com/watch?v=3jP2o9KXunA, https://github.com/qq456cvb/CanonicalVoting, https://mp.weixin.qq.com/s/L_F28IFLXvs5R4V9TTUpRw, https://github.com/Arthur151/Relative_Human, https://www.youtube.com/watch?v=Q62fj_6AxRI, https://github.com/facebookresearch/banmo, https://mp.weixin.qq.com/s/NMHP8-xWwrX40vpGx55Qew, https://sites.google.com/tri.global/depthformer, https://github.com/voldemortX/pytorch-auto-drive, https://user-images.githubusercontent.com/32259501/148680744-a18793cd-f437-461f-8c3a-b909c9931709.mp4, https://github.com/DQiaole/ZITS_inpainting, https://kaust-cair.s3.amazonaws.com/stylegan-v/stylegan-v.mp4, https://github.com/Gait3D/Gait3D-Benchmark, https://www.youtube.com/watch?v=ZqgiTLcNcks, https://github.com/lilygeorgescu/UBnormal, https://github.com/joellliu/SegmentAndComplete, https://github.com/zh460045050/DA-WSOL_CVPR2022, https://github.com/nie-lang/DeepRectangling, https://mp.weixin.qq.com/s/lp5AnrtO_9urp-Fv6Z0l2Q, https://svip-lab.github.io/dataset/RepCount_dataset.html, https://github.com/sumitramalagi/Unseen-classes-at-a-later-time, https://github.com/mapooon/SelfBlendedImages, https://github.com/charigyang/itsabouttime, https://github.com/google-research/kubric, https://mp.weixin.qq.com/s/mJ8HzY6C0GifxsErJIS3Mg, https://ai.stanford.edu/~rhgao/objectfolder2.0/, https://chenyanglei.github.io/sfpwild/index.html, https://github.com/yizhiwang96/TextLogoLayout, https://github.com/jiawei-ren/BalancedMSE, https://github.com/bmlklwx/EMS-superquadric_fitting, https://github.com/YoadTew/zero-shot-image-to-text, https://github.com/archmaester/proto2proto, https://light-field-neural-rendering.github.io/, https://github.com/google-research/google-research/tree/master/light_field_neural_rendering, [(Video Generation)](#Video Generation). Variational Transformer Networks for Layout Generation, 8. VarifocalNet: An IoU-aware Dense Object Detector, 16. DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation, 5. Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs, 36. Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking, Paper(Oral): https://arxiv.org/abs/2103.11681, Code: https://github.com/594422814/TransformerTrack, 17. Cvpr 2023 openihu/CVPR2022-Papers-with-Code: CVPR 2022 (papers with code Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework, 42. Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation, SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data, Few-Shot 3D Point Cloud Semantic Segmentation, CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching, ReDet: A Rotation-Equivariant Detector for Aerial Object Detection, Combining Semantic Guidance and Deep Reinforcement Learning for Generating Human Level Paintings, Keep Your Eyes on the Lane: Real-Time Attention-Guided Lane Detection, Involution: Inverting the Inherence of Convolution for Visual Recognition, QPIC: Query-Based Pairwise Human-Object Interaction Detection With Image-Wide Contextual Information, AQD: Towards Accurate Quantized Object Detection, Self-Supervised Learning of Depth Inference for Multi-View Stereo, Learning To Predict Visual Attributes in the Wild, ST3D: Self-Training for Unsupervised Domain Adaptation on 3D Object Detection, DG-Font: Deformable Generative Networks for Unsupervised Font Generation, Deeply Shape-Guided Cascade for Instance Segmentation. Rank the papers accepted to CVPR 2019 by the number of stars in their github repository GitHub - amusi/CVPR2021-Code: CVPR 2021 (paper with code) More than 83 million people use GitHub to discover, fork, and contribute to over 200 million projects. / (Text Detection/Recognition) 11. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. #CVPR2022 Check out one of our recent CVPR-2022 papers on Scene-Level Sketch-Based Image Retrieval. . Interactive Self-Training With Mean Teachers for Semi-Supervised Object Detection, 41. How Useful Is Self-Supervised Pretraining for Visual Tasks? SSAN: Separable Self-Attention Network for Video Representation Learning, 43. Depth From Camera Motion and Object Detection, 54. Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation, 30. Copyright and all rights therein are retained by authors or by other copyright holders. Self-Supervised Video Hashing via Bidirectional Transformers, 35. GitHub is where people build software. Paper(Oral): https://openaccess.thecvf.com/content/CVPR2021/papers/Pandey_Generalization_on_Unseen_Domains_via_Inference-Time_Label-Preserving_Target_Projections_CVPR_2021_paper.pdf; Code: https://github.com/VSumanth99/InferenceTimeDG; Generalizable Person Re-identification with Relevance-aware Mixture of Experts. Kaleido-BERTVision-Language Pre-training on Fashion Domain, 4. OTA: Optimal Transport Assignment for Object Detection, Code: https://github.com/Megvii-BaseDetection/OTA, 17. CVPR 2022 Papers with Code/Data - Paper Digest Accurate Few-Shot Object Detection With Support-Query Mutual Guidance and Hybrid Loss, Paper: https://openaccess.thecvf.com/content/CVPR2021/html/Zhang_Accurate_Few-Shot_Object_Detection_With_Support-Query_Mutual_Guidance_and_Hybrid_CVPR_2021_paper.html, 27. TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style, Object-Occluded Human Shape and Pose Estimation From a Single Color Image, Learning Fast and Robust Target Models for Video Object Segmentation, Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting, Quasi-Newton Solver for Robust Non-Rigid Registration, Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives, Deep Image Spatial Transformation for Person Image Generation, Recurrent Feature Reasoning for Image Inpainting, Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation, Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression, MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation, End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization, ARShadowGAN: Shadow Generative Adversarial Network for Augmented Reality in Single Light Scenes, Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation, StarGAN v2: Diverse Image Synthesis for Multiple Domains, Multi-Scale Progressive Fusion Network for Single Image Deraining, DoveNet: Deep Image Harmonization via Domain Verification, Noise Robust Generative Adversarial Networks, Deep Snake for Real-Time Instance Segmentation, Learning Dynamic Routing for Semantic Segmentation, Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence, F-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation, Self-Supervised Learning of Interpretable Keypoints From Unlabelled Videos, Exploit Clues From Views: Self-Supervised and Regularized Learning for Multiview Object Recognition, Unsupervised Learning of Intrinsic Structural Representation Points, Interactive Two-Stream Decoder for Accurate and Fast Saliency Detection, Towards Better Generalization: Joint Depth-Pose Learning Without PoseNet, Hyperbolic Visual Embedding Learning for Zero-Shot Recognition, MineGAN: Effective Knowledge Transfer From GANs to Target Domains With Few Images, Multi-Scale Interactive Network for Salient Object Detection, Action Segmentation With Joint Self-Supervised Temporal Domain Adaptation, Probability Weighted Compact Feature for Domain Adaptive Retrieval, Evade Deep Image Retrieval by Stashing Private Images in the Hash Space, Advisable Learning for Self-Driving Vehicles by Internalizing Observation-to-Action Rules, Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection, BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition, Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagation, Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection, PointRend: Image Segmentation As Rendering, ABCNet: Real-Time Scene Text Spotting With Adaptive Bezier-Curve Network, Say As You Wish: Fine-Grained Control of Image Caption Generation With Abstract Scene Graphs, REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments, Learning to Structure an Image With Few Colors, G-TAD: Sub-Graph Localization for Temporal Action Detection, Detailed 2D-3D Joint Representation for Human-Object Interaction, Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification, Neural Architecture Search for Lightweight Non-Local Networks, Memory Enhanced Global-Local Aggregation for Video Object Detection, Counting Out Time: Class Agnostic Video Repetition Counting in the Wild, MLCVNet: Multi-Level Context VoteNet for 3D Object Detection, Referring Image Segmentation via Cross-Modal Progressive Comprehension, CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection, Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation, Meshed-Memory Transformer for Image Captioning, Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection, Densely Connected Search Space for More Flexible Neural Architecture Search, Fine-Grained Video-Text Retrieval With Hierarchical Graph Reasoning, Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio, LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation, Graph Structured Network for Image-Text Matching, X-Linear Attention Networks for Image Captioning, Overcoming Classifier Imbalance for Long-Tail Object Detection With Balanced Group Softmax, SESS: Self-Ensembling Semi-Supervised 3D Object Detection, TITAN: Future Forecast Using Action Priors, UNAS: Differentiable Architecture Search Meets Reinforcement Learning, ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning, Symmetry and Group in Attribute-Object Compositions, Rethinking Performance Estimation in Neural Architecture Search, MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Birds Eye View Maps, Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection, D2Det: Towards High Quality Object Detection and Instance Segmentation, MTL-NAS: Task-Agnostic Neural Architecture Search Towards General-Purpose Multi-Task Learning, Prime Sample Attention in Object Detection, SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization, KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects, PVN3D: A Deep Point-Wise 3D Keypoints Voting Network for 6DoF Pose Estimation, Equalization Loss for Long-Tailed Object Recognition, Learning Depth-Guided Convolutions for Monocular 3D Object Detection, Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather, Train in Germany, Test in the USA: Making 3D Object Detectors Generalize, Exploring Categorical Regularization for Domain Adaptive Object Detection, Pose-Guided Visible Part Matching for Occluded Person ReID, ContourNet: Taking a Further Step Toward Accurate Arbitrary-Shaped Scene Text Detection, Look-Into-Object: Self-Supervised Structure Modeling for Object Recognition, RPM-Net: Robust Point Matching Using Learned Features, AutoTrack: Towards High-Performance Visual Tracking for UAV With Automatic Spatio-Temporal Regularization, Inferring Attention Shift Ranks of Objects for Image Saliency, Learning to Segment 3D Point Clouds in 2D Image Space, Cross-Domain Detection via Graph-Induced Prototype Alignment, Distilling Cross-Task Knowledge via Relationship Matching, Gradually Vanishing Bridge for Adversarial Domain Adaptation, Inter-Region Affinity Distillation for Road Marking Segmentation, DSGN: Deep Stereo Geometry Network for 3D Object Detection, Weakly-Supervised Salient Object Detection via Scribble Annotations, JA-POLS: A Moving-Camera Background Model via Joint Alignment and Partially-Overlapping Local Subspaces, AugFPN: Improving Multi-Scale Feature Learning for Object Detection, xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation, Instance Credibility Inference for Few-Shot Learning, Cross-Domain Document Object Detection: Benchmark Suite and Method, FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions, Putting Visual Object Recognition in Context, IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving, ZeroQ: A Novel Zero Shot Quantization Framework, Background Data Resampling for Outlier-Aware Classification, Scale-Equalizing Pyramid Convolution for Object Detection, Attentive Weights Generation for Few Shot Learning via Information Maximization, Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification, Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation, Learning Selective Self-Mutual Attention for RGB-D Saliency Detection, Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data, CenterMask: Real-Time Anchor-Free Instance Segmentation, FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation, Learning to Evaluate Perception Models Using Planner-Centric Metrics, Learning a Unified Sample Weighting Network for Object Detection, GaitPart: Temporal Part-Based Model for Gait Recognition, Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition, Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction, Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors, Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization, OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold, Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets, Category-Level Articulated Object Pose Estimation, GAN Compression: Efficient Architectures for Interactive Conditional GANs, Differentiable Adaptive Computation Time for Visual Reasoning, CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus, Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution, Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang, Maosen Li, Siheng Chen, Yangheng Zhao, Ya Zhang, Yanfeng Wang, Qi Tian, Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash, Heiko Hoffmann, Hongjun Wang, Guangrun Wang, Ya Li, Dongyu Zhang, Liang Lin, Yancheng Wang, Yang Xiao, Fu Xiong, Wenxiang Jiang, Zhiguo Cao, Joey Tianyi Zhou, Junsong Yuan, Minghao Guo, Yuzhe Yang, Rui Xu, Ziwei Liu, Dahua Lin, Huaidong Zhang, Xuemiao Xu, Guoqiang Han, Shengfeng He, Weifeng Chen, Shengyi Qian, David Fan, Noriyuki Kojima, Max Hamilton, Jia Deng, Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang, Xueying Wang, Yudong Guo, Bailin Deng, Juyong Zhang, Xiaogang Wang, Marcelo H. Ang Jr., Gim Hee Lee, Bin Yan, Dong Wang, Huchuan Lu, Xiaoyun Yang, Maxim Maximov, Kevin Galim, Laura Leal-Taixe, Xianhang Li, Yali Wang, Zhipeng Zhou, Yu Qiao, Teng Long, Pascal Mettes, Heng Tao Shen, Cees G. M. Snoek, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro, Hanting Chen, Yunhe Wang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu, Ting-Wu Chin, Ruizhou Ding, Cha Zhang, Diana Marculescu, Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, Ling Shao, Kai Han, Yunhe Wang, Qi Tian, Jianyuan Guo, Chunjing Xu, Chang Xu, Zan Gojcic, Caifa Zhou, Jan D. Wegner, Leonidas J. Guibas, Tolga Birdal, Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, Long Quan, Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang, Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang, Xiaodan Liang, Liang Lin, Xiaojun Chang, Shaifali Parashar, Mathieu Salzmann, Pascal Fua, Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen, Zhe Zhang, Chunyu Wang, Wenhu Qin, Wenjun Zeng, Malte Pedersen, Joakim Bruslund Haurum, Stefan Hein Bengtson, Thomas B. Moeslund, Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov, Xiaodong Gu, Zhiwen Fan, Siyu Zhu, Zuozhuo Dai, Feitong Tan, Ping Tan, Thomas Schops, Viktor Larsson, Marc Pollefeys, Torsten Sattler, Tobias Weyand, Andre Araujo, Bingyi Cao, Jack Sim, Xi Yang, Ding Xia, Taichi Kin, Takeo Igarashi, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao, Xiaoming Li, Wenyu Li, Dongwei Ren, Hongzhi Zhang, Meng Wang, Wangmeng Zuo, Deng-Ping Fan, Ge-Peng Ji, Guolei Sun, Ming-Ming Cheng, Jianbing Shen, Ling Shao, Yuming Shen, Jie Qin, Jiaxin Chen, Mengyang Yu, Li Liu, Fan Zhu, Fumin Shen, Ling Shao, Xiang Li, Tianhan Wei, Yau Pun Chen, Yu-Wing Tai, Chi-Keung Tang, Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao, Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Xin Jin, Zhibo Chen, Xueyang Wang, Xiya Zhang, Yinheng Zhu, Yuchen Guo, Xiaoyun Yuan, Liuyu Xiang, Zerun Wang, Guiguang Ding, David Brady, Qionghai Dai, Lu Fang, Long Chen, Haizhou Ai, Rui Chen, Zijie Zhuang, Shuang Liu, Dongwei Ren, Kai Zhang, Qilong Wang, Qinghua Hu, Wangmeng Zuo, Yapeng Tian, Yulun Zhang, Yun Fu, Chenliang Xu, Chenyan Wu, Yukun Chen, Jiajia Luo, Che-Chun Su, Anuja Dawane, Bikramjot Hanzra, Zhuo Deng, Bilan Liu, James Z. Wang, Cheng-hao Kuo, Zhenqiang Ying, Haoran Niu, Praful Gupta, Dhruv Mahajan, Deepti Ghadiyaram, Alan Bovik, Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, Zhou Wang, Xin Lin, Changxing Ding, Jinquan Zeng, Dacheng Tao, Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, In So Kweon, Li Wang, Dong Li, Yousong Zhu, Lu Tian, Yi Shan, Yifeng Chen, Guangchen Lin, Songyuan Li, Omar Bourahla, Yiming Wu, Fangfang Wang, Junyi Feng, Mingliang Xu, Xi Li, Jie Song, Yixin Chen, Jingwen Ye, Xinchao Wang, Chengchao Shen, Feng Mao, Mingli Song, Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian, Siva Karthik Mustikovela, Varun Jampani, Shalini De Mello, Sifei Liu, Umar Iqbal, Carsten Rother, Jan Kautz, Qibin Hou, Li Zhang, Ming-Ming Cheng, Jiashi Feng, Qi Fan, Wei Zhuo, Chi-Keung Tang, Yu-Wing Tai, Tiancai Wang, Tong Yang, Martin Danelljan, Fahad Shahbaz Khan, Xiangyu Zhang, Jian Sun, Christian Simon, Piotr Koniusz, Richard Nock, Mehrtash Harandi, Yaxing Wang, Salman Khan, Abel Gonzalez-Garcia, Joost van de Weijer, Fahad Shahbaz Khan, Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, Xiaowei Li, Antigoni Tsiami, Petros Koutras, Petros Maragos, Xingtong Liu, Yiping Zheng, Benjamin Killeen, Masaru Ishii, Gregory D. Hager, Russell H. Taylor, Mathias Unberath, Jiayu Yang, Wei Mao, Jose M. Alvarez, Miaomiao Liu, Dominik Kulon, Riza Alp Guler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou, Zezheng Wang, Zitong Yu, Chenxu Zhao, Xiangyu Zhu, Yunxiao Qin, Qiusheng Zhou, Feng Zhou, Zhen Lei, Ruixu Liu, Ju Shen, He Wang, Chen Chen, Sen-ching Cheung, Vijayan Asari, Wang Shen, Wenbo Bao, Guangtao Zhai, Li Chen, Xiongkuo Min, Zhiyong Gao, Wentao Jiang, Si Liu, Chen Gao, Jie Cao, Ran He, Jiashi Feng, Shuicheng Yan, Muhammed Kocabas, Nikos Athanasiou, Michael J. Distillation with Context-aware Aggregation for Few-Shot Semantic Segmentation with Realistic Annotation Costs 36. Commands accept both tag and branch names, so creating this branch may cause unexpected behavior Paper Oral. Network Topology Search for 3D Medical Image Segmentation, 31, it would be helpful have! 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