329 citations · 392 across the 5 of their papers we have counts for
5 papers
Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints
Ruoyu Chen, Shangquan Sun, Xiaoqing Guo +8
Reliable models should not only predict correctly, but also base their decisions on acceptable evidence. However, conventional supervised learning typically provides only class-lev…
Exploring the Robustness of Human Parsers Towards Common Corruptions
Sanyi Zhang, Xiaochun Cao, Rui Wang +2
Human parsing aims to segment each pixel of the human image with fine-grained semantic categories. However, current human parsers trained with clean data are easily confused by num…
Frequency Perception Network for Camouflaged Object Detection
Runmin Cong, Mengyao Sun, Sanyi Zhang +3
Camouflaged object detection (COD) aims to accurately detect objects hidden in the surrounding environment. However, the existing COD methods mainly locate camouflaged objects in t…
AIParsing: Anchor-free Instance-level Human Parsing
Sanyi Zhang, Xiaochun Cao, Guo-Jun Qi +2
Most state-of-the-art instance-level human parsing models adopt two-stage anchor-based detectors and, therefore, cannot avoid the heuristic anchor box design and the lack of analys…
Nested Network with Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images
Chongyi Li, Runmin Cong, Junhui Hou +3
Arising from the various object types and scales, diverse imaging orientations, and cluttered backgrounds in optical remote sensing image (RSI), it is difficult to directly extend…