Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondence

Deep Translation Prior: Test-time Training for Photorealistic Style Transfer

Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledge

Pyramidal Semantic Correspondence Networks

CATs: Cost Aggregation Transformers for Visual Correspondence

Learning Adversarial Confidence Measures for Robust Stereo Matching

Deep Matching Prior: Test-Time Optimization for Dense Correspondence

Learning Canonical 3D Object Representation for Fine-grained Recognition

Adaptive Confidence Thresholding for Monocular Depth Estimation

Hough Contrastive Learning: Hough Voting to Find Better Positive Pairs in Dense Self-supervised Representation Learning