CVPR2021 最全整理：论文分类汇总 / 代码 / 项目 / 论文解读（更新中）【计算机视觉】

作为计算机视觉领域三大顶会之一，CVPR2021目前已公布了所有接收论文ID，一共有1663篇论文被接收，接收率为23.7%，虽然接受率相比去年有所上升，但竞争也是非常激烈，相关报道：CVPR 2021接收结果出炉！录用1663篇，接受率提升，你的论文中了吗？。

在本文中，我们对CVPR2021的最新论文进行了分类汇总，并将对优秀论文解读报道和技术直播。我们将对CVPR2021顶会论文进行实时跟进和分类，欢迎点击文末关注按钮，即可获取本帖最新更新消息。

此前我们也对CVPR2020、CVPR2019的论文进行了整理，做了分类汇总，点击下列推文即可前往：

所有关于CVPR的论文整理都汇总在了我们的Github项目中，该项目目前已收获6100 Star。
Github项目地址：https://github.com/extreme-assistant/CVPR2021-Paper-Code-Interpretation

CVPR2021同系列整理：

下文为对CVPR2021论文的分方向整理：

分类目录：

1. 检测

2. 图像分割(Image Segmentation)

3. 图像处理(Image Processing)

4. 估计(Estimation)

5. 图像/视频检索(Image Retrieval)

6. 人脸(Face)

7. 目标跟踪(Object Tracking)

8. 医学影像(Medical Imaging)

9. 文本检测/识别(Text Detection/Recognition)

10. 遥感图像(Remote Sensing Image)

11. GAN/生成式/对抗式(GAN/Generative/Adversarial)

12. 三维视觉(3D Vision)

13. 神经网络架构(Neural Network Structure)

14. 神经网络架构搜索(NAS)

15. 数据处理(Data Processing)

16. 模型压缩(Model Compression)

• 知识蒸馏(Knowledge Distillation)

17. 模型评估(Model Evaluation)

18. 数据集(Database)

19. 主动学习(Active Learning)

20. 小样本/零样本学习(Few-shot/Zero-shot Learning)

21. 持续学习(Continual Learning/Life-long Learning)

22. 视觉推理(Visual Reasoning)

23. 迁移学习/domain/自适应

24. 对比学习(Contrastive Learning)

25. 强化学习(Reinforcement Learning)

暂无分类

图像目标检测(Image Object Detection)

[9] MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection(用于类别识别无监督域自适应对象检测)

paper

[8] OPANAS: One-Shot Path Aggregation Network Architecture Search for Object(一键式路径聚合网络体系结构搜索对象)

paper|code

[7] Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection(小样本目标检测的语义关系推理)

paper

[6] General Instance Distillation for Object Detection(通用实例蒸馏技术在目标检测中的应用)

paper

[5] Instance Localization for Self-supervised Detection Pretraining(自监督检测预训练的实例定位)

paper｜code

[4] Multiple Instance Active Learning for Object Detection（用于对象检测的多实例主动学习）

paper|code

[3] Towards Open World Object Detection(开放世界中的目标检测)

paper|code

[2] Positive-Unlabeled Data Purification in the Wild for Object Detection(野外检测对象的阳性无标签数据提纯)

[1] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

paper|code

解读：无监督预训练检测器

视频目标检测(Video Object Detection)

[3] Depth from Camera Motion and Object Detection(相机运动和物体检测的深度)

paper

[2] There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge(多模态知识提取的自监督多目标检测与有声跟踪)

paper|video|project

[1] Dogfight: Detecting Drones from Drone Videos（从无人机视频中检测无人机）

三维目标检测(3D object detection)

[2] 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection(利用IoU预测进行半监督3D对象检测)

paper|code|project|video

[1] Categorical Depth Distribution Network for Monocular 3D Object Detection(用于单目三维目标检测的分类深度分布网络)

paper

动作检测(Activity Detection)

[1] Coarse-Fine Networks for Temporal Activity Detection in Videos

paper

异常检测(Anomally Detection)

[1] Multiresolution Knowledge Distillation for Anomaly Detection(用于异常检测的多分辨率知识蒸馏)

paper

人物交互检测(HOI Detection)

[1] End-to-End Human Object Interaction Detection with HOI Transformer(使用HOI Transformer进行端到端的人类对象交互检测)

paper|code

伪装目标检测(Camouflaged Object Detection)

[1] Simultaneously Localize, Segment and Rank the Camouflaged Objects(同时定位，分割和排序伪装的对象)

paper|code

图像分割(Image Segmentation)

[2] Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

paper|code

[1] PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation(语义流经点以进行航空图像分割)

全景分割(Panoptic Segmentation)

[2] Cross-View Regularization for Domain Adaptive Panoptic Segmentation(用于域自适应全景分割的跨视图正则化)

paper

[1] 4D Panoptic LiDAR Segmentation（4D全景LiDAR分割）

paper

语义分割(Semantic Segmentation)

[5] Learning Statistical Texture for Semantic Segmentation(学习用于语义分割的统计纹理)

paper

[4] Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation(基于双层域混合的半监督域自适应语义分割)

paper

[3] Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation(多源领域自适应与协作学习的语义分割)

paper

[2] Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges(走向城市规模3D点云的语义分割：数据集，基准和挑战)

paper|code

[1] PLOP: Learning without Forgetting for Continual Semantic Segmentation（PLOP：学习而不会忘记连续的语义分割）

paper

实例分割(Instance Segmentation)

[1] End-to-End Video Instance Segmentation with Transformers(使用Transformer的端到端视频实例分割)

paper

抠图(Matting)

[1] Real-Time High Resolution Background Matting

paper|code|project|video

9. 估计(Estimation)

人体姿态估计(Human Pose Estimation)

[3] Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing(用于实例感知人类语义解析的可微分多粒度人类表示学习)

paper|code

[2] CanonPose: Self-supervised Monocular 3D Human Pose Estimation in the Wild（野外自监督的单眼3D人类姿态估计）

[1] PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers（具有透视作物层的3D姿势的几何感知神经重建）

paper

手势估计(Gesture Estimation)

[1] Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration(基于语义聚合和自适应2D-1D配准的相机空间手部网格恢复)

paper|code

光流/位姿/运动估计(Flow/Pose/Motion Estimation)

[3] GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation(用于单眼6D对象姿态估计的几何引导直接回归网络)

paper|code

[2] Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments(在动态室内环境中，通过空间划分的鲁棒神经路由可实现摄像机的重新定位)

paper|project

[1] MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization(通过3D扫描同步进行多主体分割和运动估计)

paper|code

深度估计(Depth Estimation)

图像处理(Image Processing)

图像复原(Image Restoration)/超分辨率(Super Resolution)

[5] ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic(通过数据特征加速超分辨率网络的通用框架)

paper

[4] Learning Continuous Image Representation with Local Implicit Image Function(通过局部隐含图像功能学习连续图像表示)

paepr|code|video|project

[3] Multi-Stage Progressive Image Restoration(多阶段渐进式图像复原)

paper|code

[2] Data-Free Knowledge Distillation For Image Super-Resolution(DAFL算法的SR版本)

[1] AdderSR: Towards Energy Efficient Image Super-Resolution(将加法网路应用到图像超分辨率中)

paper|code

解读：华为开源加法神经网络

图像去阴影/去反射(Image Shadow Removal/Image Reflection Removal)

[2] Robust Reflection Removal with Reflection-free Flash-only Cues(通过无反射的仅含Flash线索进行鲁棒的反射去除)

paper|code

[1] Auto-Exposure Fusion for Single-Image Shadow Removal(用于单幅图像阴影去除的自动曝光融合)

paper|code

图像去噪/去模糊/去雨去雾(Image Denoising)

[2] ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring(学习用于视频去模糊的全范围体积对应)

paper

[1] DeFMO: Deblurring and Shape Recovery of Fast Moving Objects(快速移动物体的去模糊和形状恢复)

paper|code|video

图像编辑/图像修复(Image Edit/Inpainting)

[5] PISE: Person Image Synthesis and Editing with Decoupled GAN(使用分离的GAN进行人像合成和编辑)

paper|code

[4] DeFLOCNet: Deep Image Editing via Flexible Low level Controls(通过灵活的低级控件进行深度图像编辑)

[3] PD-GAN: Probabilistic Diverse GAN for Image Inpainting(用于图像修复的概率多样GAN)

[2] Anycost GANs for Interactive Image Synthesis and Editing(用于交互式图像合成和编辑的AnyCost Gans)

paper|code

[1] Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing（利用GAN中潜在的空间维度进行实时图像编辑）

图像翻译（Image Translation）

[3] Spatially-Adaptive Pixelwise Networks for Fast Image Translation(空间自适应像素网络，用于快速图像翻译)

paper|project

[2] Image-to-image Translation via Hierarchical Style Disentanglement

paper|code

[1] Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation(样式编码：用于图像到图像翻译的StyleGAN编码器)

paper|code|project

人脸(Face)

[8] Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders(分析和改进自省变分自动编码器)

paper|code|project

[7] PISE: Person Image Synthesis and Editing with Decoupled GAN(使用分离的GAN进行人像合成和编辑)

paper|code

[6] WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition(揭示了百万级深度人脸识别力量的基准测试)

paper|benchmark

[5] Cross Modal Focal Loss for RGBD Face Anti-Spoofing(跨模态焦点损失，用于RGBD人脸反欺骗)
paper

[4] When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework(当年龄不变的人脸识别遇到人脸年龄合成时：一个多任务学习框架)

paper|code

[3] Multi-attentional Deepfake Detection(多注意的深伪检测)

paper

[2] Image-to-image Translation via Hierarchical Style Disentanglement

paper|code

[1] A 3D GAN for Improved Large-pose Facial Recognition(用于改善大姿势面部识别的3D GAN)

paper

目标跟踪(Object Tracking)

[4] HPS: localizing and tracking people in large 3D scenes from wearable sensors(通过可穿戴式传感器对大型3D场景中的人进行定位和跟踪)

[3] Track to Detect and Segment: An Online Multi-Object Tracker(跟踪检测和分段：在线多对象跟踪器)

project|video

[2] Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking(多目标跟踪的概率小波计分和修复)

paper

[1] Rotation Equivariant Siamese Networks for Tracking（旋转等距连体网络进行跟踪）

paper

图像/视频检索(Image/Video Retrieval)

[1] QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval(实用的查询高效的图像检索黑盒攻击)

paper

行为识别/动作识别(Action/Activity Recognition)

[1] Behavior-Driven Synthesis of Human Dynamics(行为驱动的人类动力学综合)

paper|code<>

[3] Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification(基于视频的人员重新识别的全球指导对等学习)

paper

[2] Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification(联合抗噪学习和元相机移位自适应，用于无监督人员的重新识别)

paper

[1] Meta Batch-Instance Normalization for Generalizable Person Re-Identification(通用批处理人员重新标识的元批实例规范化)

paper

医学影像(Medical Imaging)

[5] DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images(一种心脏标记磁共振图像运动跟踪的无监督深度学习方法)

paper

[4] Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning(多机构协作改进基于深度学习的联合学习磁共振图像重建)

paper|code

[3] 3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management(用于胰腺肿块分割，诊断和定量患者管理的3D图形解剖学几何集成网络)

[2] Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies(深部病变追踪器：在4D纵向成像研究中监控病变)

paper

[1] Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization(通过脊柱矫正和解剖学约束优化在CT中自动进行椎骨定位和识别)

paper

文本检测/识别(Text Detection/Recognition)

[1] What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels(如果我们仅将真实数据集用于场景文本识别该怎么办？ 带有较少标签的场景文本识别)

paepr|code

遥感图像(Remote Sensing Image)

[1] Deep Gradient Projection Networks for Pan-sharpening(【超分辨率】泛锐化的深梯度投影网络)

paper|code

神经网络架构搜索(NAS)

[4] OPANAS: One-Shot Path Aggregation Network Architecture Search for Object(一键式路径聚合网络体系结构搜索对象)

paper|code

[3] AttentiveNAS: Improving Neural Architecture Search via Attentive(通过注意力改善神经架构搜索)

paper

[2] ReNAS: Relativistic Evaluation of Neural Architecture Search(NAS predictor当中ranking loss的重要性)

paper

[1] HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens（降低NAS的成本）

paper

GAN/生成式/对抗式(GAN/Generative/Adversarial)

[11] Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders(分析和改进自省变分自动编码器)

paper|code|project

[10] LOHO: Latent Optimization of Hairstyles via Orthogonalization(LOHO：通过正交化潜在地优化发型)

paper

[9] PISE: Person Image Synthesis and Editing with Decoupled GAN(使用分离的GAN进行人像合成和编辑)

paper|code

[8] Closed-Form Factorization of Latent Semantics in GANs(GAN中潜在语义的闭式分解)

paper|code

[7] PD-GAN: Probabilistic Diverse GAN for Image Inpainting(用于图像修复的概率多样GAN)

[6] Anycost GANs for Interactive Image Synthesis and Editing(用于交互式图像合成和编辑的AnyCost Gans)

paper|code

[5] Efficient Conditional GAN Transfer with Knowledge Propagation across Classes(高效的有条件GAN转移以及跨课程的知识传播)

paper|code

[4] Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing（利用GAN中潜在的空间维度进行实时图像编辑）

[3] Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs(Hijack-GAN：意外使用经过预训练的黑匣子GAN)

paper

[2] Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation(样式编码：用于图像到图像翻译的StyleGAN编码器)

paper|code|project

[1] A 3D GAN for Improved Large-pose Facial Recognition(用于改善大姿势面部识别的3D GAN)

paper

三维视觉(3D Vision)

[2] A Deep Emulator for Secondary Motion of 3D Characters(三维角色二次运动的深度仿真器)
paper

[1] 3D CNNs with Adaptive Temporal Feature Resolutions(具有自适应时间特征分辨率的3D CNN)

paper

点云(Point Cloud)

[9] Robust Point Cloud Registration Framework Based on Deep Graph Matching(基于深度图匹配的鲁棒点云配准框架)

paper|code

[8] TPCN: Temporal Point Cloud Networks for Motion Forecasting(面向运动预测的时态点云网络)
paper|[code]()

[7] PointGuard: Provably Robust 3D Point Cloud Classification(可证明稳健的三维点云分类)

paper

[6] Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges(走向城市规模3D点云的语义分割：数据集，基准和挑战)

paper|code

[5] SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration(SpinNet：学习用于3D点云配准的通用表面描述符)

paper|code

[4] MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization(通过3D扫描同步进行多主体分割和运动估计)

paper|code

[3] Diffusion Probabilistic Models for 3D Point Cloud Generation(三维点云生成的扩散概率模型)

paper|code

[2] Style-based Point Generator with Adversarial Rendering for Point Cloud Completion(用于点云补全的对抗性渲染基于样式的点生成器)

paper

[1] PREDATOR: Registration of 3D Point Clouds with Low Overlap(预测器：低重叠的3D点云的配准)

paper|code|project

三维重建(3D Reconstruction)

[1] PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers（具有透视作物层的3D姿势的几何感知神经重建）

paper

模型压缩(Model Compression)

[2] Manifold Regularized Dynamic Network Pruning（动态剪枝的过程中考虑样本复杂度与网络复杂度的约束）

[1] Learning Student Networks in the Wild（一种不需要原始训练数据的模型压缩和加速技术）

paper|code

解读：华为诺亚方舟实验室提出无需数据网络压缩技术

知识蒸馏(Knowledge Distillation)

[5] Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning(少班级增量学习的语义感知知识蒸馏)

paper

[4] Teachers Do More Than Teach: Compressing Image-to-Image Models(https://arxiv.org/abs/2103.03467)

paper|code

[3] General Instance Distillation for Object Detection(通用实例蒸馏技术在目标检测中的应用)

paper

[2] Multiresolution Knowledge Distillation for Anomaly Detection(用于异常检测的多分辨率知识蒸馏)

paper

[1] Distilling Object Detectors via Decoupled Features（前景背景分离的蒸馏技术）

神经网络架构(Neural Network Structure)

[4] Coordinate Attention for Efficient Mobile Network Design(协调注意力以实现高效的移动网络设计)

paper

[3] Rethinking Channel Dimensions for Efficient Model Design(重新考虑通道尺寸以进行有效的模型设计)

paper|code

[2] Inverting the Inherence of Convolution for Visual Recognition（颠倒卷积的固有性以进行视觉识别）

[1] RepVGG: Making VGG-style ConvNets Great Again

paper|code

解读：RepVGG：极简架构，SOTA性能，让VGG式模型再次伟大

Transformer

[3] Transformer Interpretability Beyond Attention Visualization(注意力可视化之外的Transformer可解释性)

paper|code

[2] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

paper|code

解读：无监督预训练检测器

[1] Pre-Trained Image Processing Transformer(底层视觉预训练模型)

paper

图神经网络(GNN)

[2] Quantifying Explainers of Graph Neural Networks in Computational Pathology(计算病理学中图神经网络的量化解释器)

paper

[1] Sequential Graph Convolutional Network for Active Learning(主动学习的顺序图卷积网络)

paper

数据处理(Data Processing)

数据增广(Data Augmentation)

[1] KeepAugment: A Simple Information-Preserving Data Augmentation(一种简单的保存信息的数据扩充)

paper

表征学习(Representation Learning)

[1] VirTex: Learning Visual Representations from Textual Annotations（【表示学习】从文本注释中学习视觉表示）

paper|code

归一化/正则化(Batch Normalization)

[3] Adaptive Consistency Regularization for Semi-Supervised Transfer Learning(半监督转移学习的自适应一致性正则化)

paper|code

[2] Meta Batch-Instance Normalization for Generalizable Person Re-Identification(通用批处理人员重新标识的元批实例规范化)

paper

[1] Representative Batch Normalization with Feature Calibration（具有特征校准功能的代表性批量归一化）

图像聚类(Image Clustering)

[2] Improving Unsupervised Image Clustering With Robust Learning（通过鲁棒学习改善无监督图像聚类）

paper|code

[1] Reconsidering Representation Alignment for Multi-view Clustering(重新考虑多视图聚类的表示对齐方式)

模型评估(Model Evaluation)

[1] Are Labels Necessary for Classifier Accuracy Evaluation?(测试集没有标签，我们可以拿来测试模型吗？)

paper|解读

数据集(Database)

[2] Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges(走向城市规模3D点云的语义分割：数据集，基准和挑战)

paper|code

[1] Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels（重新标记ImageNet：从单标签到多标签，从全局标签到本地标签）

paper|code

主动学习(Active Learning)

[3] Vab-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning

paper|code

[2] Multiple Instance Active Learning for Object Detection（用于对象检测的多实例主动学习）

paper|code

[1] Sequential Graph Convolutional Network for Active Learning(主动学习的顺序图卷积网络)

paper

小样本学习(Few-shot Learning)/零样本学习(Zero-shot Learning)

[6] Goal-Oriented Gaze Estimation for Zero-Shot Learning(零样本学习的目标导向注视估计)

paper|code

[5] Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

paper|code

[4] Counterfactual Zero-Shot and Open-Set Visual Recognition(反事实零射和开集视觉识别)

paper|code

[3] Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection(小样本目标检测的语义关系推理)

paper

[2] Few-shot Open-set Recognition by Transformation Consistency(转换一致性很少的开放集识别)

[1] Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning(探索少量学习的不变表示形式和等变表示形式的互补强度)

paper|

持续学习(Continual Learning/Life-long Learning)

[2] Rainbow Memory: Continual Learning with a Memory of Diverse Samples（不断学习与多样本的记忆）

[1] Learning the Superpixel in a Non-iterative and Lifelong Manner(以非迭代和终身的方式学习超像素)

视觉推理(Visual Reasoning)

[1] Transformation Driven Visual Reasoning(转型驱动的视觉推理)

paper|code|project

迁移学习/domain/自适应](#domain)

[6] Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation(基于双层域混合的半监督域自适应语义分割)

paper

[5] Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation(多源领域自适应与协作学习的语义分割)

paper

[4] Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning(通过域随机化和元学习对视觉表示进行连续调整)

paper

[3] Domain Generalization via Inference-time Label-Preserving Target Projections(基于推理时间保标目标投影的区域泛化)

paper

[2] MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing(可伸缩的自适应视频压缩传感重建)

paper|code

[1] FSDR: Frequency Space Domain Randomization for Domain Generalization(用于域推广的频域随机化)

paper

对比学习(Contrastive Learning)

[1] Fine-grained Angular Contrastive Learning with Coarse Labels(粗标签的细粒度角度对比学习)

paper

强化学习(Reinforcement Learning)

[1] Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach(无监督学习以进行稳健拟合：一种强化学习方法)


paper

Consensus Maximisation Using Influences of Monotone Boolean Functions(利用单调布尔函数的影响实现共识最大化)

paper

Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food(实现对通用食品的自动营养理解)

paper

Structured Scene Memory for Vision-Language Navigation(用于视觉语言导航的结构化场景存储器)

paper|code

Learning Asynchronous and Sparse Human-Object Interaction in Videos(视频中异步稀疏人-物交互的学习)

paper

Self-supervised Geometric Perception(自我监督的几何知觉)

paper

Quantifying Explainers of Graph Neural Networks in Computational Pathology(计算病理学中图神经网络的量化解释器)

paper

Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts(探索具有对比场景上下文的数据高效3D场景理解)

paper|project|video

Data-Free Model Extraction(无数据模型提取)

paper

Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition(用于【位置识别】的局部全局描述符的【多尺度融合】)

paper|code

Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations(适用于正确概念的权利：通过可解释性来修正神经符号概念)

paper

Multi-Objective Interpolation Training for Robustness to Label Noise(多目标插值训练的鲁棒性)

paper|code

VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs(【文本生成】VX2TEXT：基于视频的文本生成的端到端学习来自多模式输入)

paper

Scan2Cap: Context-aware Dense Captioning in RGB-D Scans(【图像字幕】Scan2Cap：RGB-D扫描中的上下文感知密集字幕)
paper|code|project|video

Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph(基于目标关系图的分层部分可观测目标驱动策略学习)

paper

ID-Unet: Iterative Soft and Hard Deformation for View Synthesis(视图合成的迭代软硬变形)

paper

PML: Progressive Margin Loss for Long-tailed Age Classification(【长尾分布】【图像分类】长尾年龄分类的累进边际损失)

paper

Diversifying Sample Generation for Data-Free Quantization（【图像生成】多样化的样本生成，实现无数据量化）

paper

Domain Generalization via Inference-time Label-Preserving Target Projections（通过保留推理时间的目标投影进行域泛化）

paper

DeRF: Decomposed Radiance Fields（分解的辐射场）

project

Densely connected multidilated convolutional networks for dense prediction tasks（【密集预测】密集连接的多重卷积网络，用于密集的预测任务）

paper

Weakly-supervised Grounded Visual Question Answering using Capsules（使用胶囊进行弱监督的地面视觉问答）

FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation（【视频插帧】FLAVR：用于快速帧插值的与流无关的视频表示）

paper|code|project

Probabilistic Embeddings for Cross-Modal Retrieval（跨模态检索的概率嵌入）

paper

Self-supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map(道路动力学和成本图的自监督式多步同时预测)

IIRC: Incremental Implicitly-Refined Classification(增量式隐式定义的分类)

paper|project

Fair Attribute Classification through Latent Space De-biasing(通过潜在空间去偏的公平属性分类)

paper|code|project

Information-Theoretic Segmentation by Inpainting Error Maximization(修复误差最大化的信息理论分割)

paper

UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pretraining(【视频语言学习】UC2：通用跨语言跨模态视觉和语言预培训)

Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling(通过稀疏采样进行视频和语言学习)

paper|code

D-NeRF: Neural Radiance Fields for Dynamic Scenes(D-NeRF：动态场景的神经辐射场)

paper|project

Weakly Supervised Learning of Rigid 3D Scene Flow(刚性3D场景流的弱监督学习)

paper|code|project

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