1.9k citations · 4.9k across the 47 of their papers we have counts for
7 papers · 1 filter
Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin Softmax
Peng Lu, Gao Huang, Hangyu Lin +3
This paper proposes a novel approach for Sketch-Based Image Retrieval (SBIR), for which the key is to bridge the gap between sketches and photos in terms of the data representation…
Anytime Stereo Image Depth Estimation on Mobile Devices
Yan Wang, Zihang Lai, Gao Huang +4
Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints. Current state-o…
Rethinking the Value of Network Pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou +2
Network pruning is widely used for reducing the heavy inference cost of deep models in low-resource settings. A typical pruning algorithm is a three-stage pipeline, i.e., training…
Interpretable Spatio-temporal Attention for Video Action Recognition
Lili Meng, Bo Zhao, Bo Chang +4
Inspired by the observation that humans are able to process videos efficiently by only paying attention where and when it is needed, we propose an interpretable and easy plug-in sp…
An empirical study on evaluation metrics of generative adversarial networks
Qiantong Xu, Gao Huang, Yang Yuan +4
Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address…
Resource Aware Person Re-identification across Multiple Resolutions
Yan Wang, Lequn Wang, Yurong You +6
Not all people are equally easy to identify: color statistics might be enough for some cases while others might require careful reasoning about high- and low-level details. However…
Horizontal Pyramid Matching for Person Re-identification
Yang Fu, Yunchao Wei, Yuqian Zhou +5
Despite the remarkable recent progress, person re-identification (Re-ID) approaches are still suffering from the failure cases where the discriminative body parts are missing. To m…