整理：AI算法与图像处理，分享请注明出处
CVPR2022论文和代码整理：https://github.com/DWCTOD/CVPR2022-Papers-with-Code-Demo
欢迎关注：
Decoupled Knowledge Distillation
- 论文/Paper：https://arxiv.org/abs/2203.08679
- 代码/Code：https://github.com/megvii-research/mdistiller
Deep vanishing point detection: Geometric priors make dataset variations vanish
- 论文/Paper：https://arxiv.org/abs/2203.08586
- 代码/Code：https://github.com/yanconglin/VanishingPoint_HoughTransform_GaussianSphere
EDTER: Edge Detection with Transformer
- 论文/Paper：https://arxiv.org/abs/2203.08566
- 代码/Code：
MonoJSG: Joint Semantic and Geometric Cost Volume for Monocular 3D Object Detection
- 论文/Paper：https://arxiv.org/abs/2203.08563
- 代码/Code：
Non-isotropy Regularization for Proxy-based Deep Metric Learning
- 论文/Paper：https://arxiv.org/abs/2203.08563
- 代码/Code：https://github.com/ExplainableML/NonIsotropicProxyDML
Integrating Language Guidance into Vision-based Deep Metric Learning
- 论文/Paper：https://arxiv.org/abs/2203.08543
- 代码/Code：https://github.com/ExplainableML/LanguageGuidance_for_DML
Scribble-Supervised LiDAR Semantic Segmentation
- 论文/Paper：https://arxiv.org/abs/2203.08537
- 代码/Code：https://github.com/ouenal/scribblekitti
Capturing Humans in Motion: Temporal-Attentive 3D Human Pose and Shape Estimation from Monocular Video
- 论文/Paper：https://arxiv.org/abs/2203.08534
- 代码/Code：https://mps-net.github.io/MPS-Net/
Towards Practical Certifiable Patch Defense with Vision Transformer
- 论文/Paper：https://arxiv.org/abs/2203.08519
- 代码/Code：
QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation
- 论文/Paperhttps://arxiv.org/abs/2203.08483
- 代码/Code：
Pseudo-Q: Generating Pseudo Language Queries for Visual Grounding
- 论文/Paper：https://arxiv.org/abs/2203.08481
- 代码/Code：https://github.com/LeapLabTHU/Pseudo-Q
The Devil Is in the Details: Window-based Attention for Image Compression
- 论文/Paper：https://arxiv.org/abs/2203.08450
- 代码/Code：https://github.com/Googolxx/STF
Attribute Group Editing for Reliable Few-shot Image Generation
- 论文/Paper：https://arxiv.org/abs/2203.08422
- 代码/Code：
Privacy-preserving Online AutoML for Domain-Specific Face Detection
- 论文/Paper：https://arxiv.org/abs/2203.08399
- 代码/Code：
Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting
- 论文/Paper：https://arxiv.org/abs/2203.08354
- 代码/Code：https://github.com/flyinglynx/Bilinear-Matching-Network
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection
- 论文/Paper：https://arxiv.org/abs/2203.08195
- 代码/Code：https://github.com/tensorflow/lingvo/tree/master/lingvo/
