6 citations · 12 across the 3 of their papers we have counts for
6 papers
Learnable Cost Volume Using the Cayley Representation
Taihong Xiao, Jinwei Yuan, Deqing Sun +4
Cost volume is an essential component of recent deep models for optical flow estimation and is usually constructed by calculating the inner product between two feature vectors. How…
Semi-Supervised Learning with Meta-Gradient
Xin-Yu Zhang, Taihong Xiao, Haolin Jia +2
In this work, we propose a simple yet effective meta-learning algorithm in semi-supervised learning. We notice that most existing consistency-based approaches suffer from overfitti…
Dependency Aware Filter Pruning
Kai Zhao, Xin-Yu Zhang, Qi Han +1
Convolutional neural networks (CNNs) are typically over-parameterized, bringing considerable computational overhead and memory footprint in inference. Pruning a proportion of unimp…
AdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning
Xin-Yu Zhang, Le Zhang, Zao-Yi Zheng +3
Triplet loss has been widely employed in a wide range of computer vision tasks, including local descriptor learning. The effectiveness of the triplet loss heavily relies on the tri…
Res2Net: A New Multi-scale Backbone Architecture
Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao +3
Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate…
DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection
Yun Liu, Ming-Ming Cheng, Xinyu Zhang +2
Recent progress on salient object detection mainly aims at exploiting how to effectively integrate multi-scale convolutional features in convolutional neural networks (CNNs). Many…