4 papers
Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer
Ziyang Chen, Wenting Li, Yongjun Zhang +4
Constrained by the low-rank bottleneck inherent in attention mechanisms, current stereo matching transformers suffer from limited nonlinear expressivity, which renders their featur…
10K is Enough: An Ultra-Lightweight Binarized Network for Infrared Small-Target Detection
Biqiao Xin, Qianchen Mao, Bingshu Wang +3
The widespread deployment of Infrared Small-Target Detection (IRSTD) algorithms on edge devices necessitates the exploration of model compression techniques. Binarized neural netwo…
MoCha-Stereo: Motif Channel Attention Network for Stereo Matching
Ziyang Chen, Wei Long, He Yao +4
Learning-based stereo matching techniques have made significant progress. However, existing methods inevitably lose geometrical structure information during the feature channel gen…
Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph
Ziyang Chen, Yongjun Zhang, Wenting Li +3
Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based stereo matching methods inheren…