3.5k citations · 3.5k across the 8 of their papers we have counts for
8 papers
On Training Implicit Models
Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai +2
This paper focuses on training implicit models of infinite layers. Specifically, previous works employ implicit differentiation and solve the exact gradient for the backward propag…
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…
Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle
Xin-Yu Zhang, Kai Zhao, Taihong Xiao +2
Recent advances in convolutional neural networks(CNNs) usually come with the expense of excessive computational overhead and memory footprint. Network compression aims to alleviate…
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…