373 citations · 1.3k across the 66 of their papers we have counts for
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Displacement-Invariant Cost Computation for Efficient Stereo Matching
Yiran Zhong, Charles Loop, Wonmin Byeon +7
Although deep learning-based methods have dominated stereo matching leaderboards by yielding unprecedented disparity accuracy, their inference time is typically slow, on the order…
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation
Jianyuan Wang, Yiran Zhong, Yuchao Dai +3
Learning matching costs has been shown to be critical to the success of the state-of-the-art deep stereo matching methods, in which 3D convolutions are applied on a 4D feature volu…
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
Dongxu Li, Chenchen Xu, Xin Yu +4
Sign language translation (SLT) aims to interpret sign video sequences into text-based natural language sentences. Sign videos consist of continuous sequences of sign gestures with…
Single Image Super-Resolution via a Holistic Attention Network
Ben Niu, Weilei Wen, Wenqi Ren +6
Informative features play a crucial role in the single image super-resolution task. Channel attention has been demonstrated to be effective for preserving information-rich features…
Deblurring by Realistic Blurring
Kaihao Zhang, Wenhan Luo, Yiran Zhong +4
Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not…
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition
Xu Li, Jingwen Wang, Lin Ma +4
Effective and Efficient spatio-temporal modeling is essential for action recognition. Existing methods suffer from the trade-off between model performance and model complexity. In…