activity
20142023
most citedNetwork Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

742 citations · 1.8k across the 57 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

cs.CV2019

Template-Instance Loss for Offline Handwritten Chinese Character Recognition

Yao Xiao, Dan Meng, Cewu Lu +1

The long-standing challenges for offline handwritten Chinese character recognition (HCCR) are twofold: Chinese characters can be very diverse and complicated while similarly lookin…

cs.CV2019★ 3 cited

DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking

Zhenmei Shi, Haoyang Fang, Yu-Wing Tai +1

Psychological studies have found that human visual tracking system involves learning, memory, and planning. Despite recent successes, not many works have focused on memory and plan…

cs.CV2019★ 37 cited

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

Qi Fan, Wei Zhuo, Chi-Keung Tang +1

Conventional methods for object detection typically require a substantial amount of training data and preparing such high-quality training data is very labor-intensive. In this pap…

cs.CV2019★ 9 cited

StableNet: Semi-Online, Multi-Scale Deep Video Stabilization

Chia-Hung Huang, Hang Yin, Yu-Wing Tai +1

Video stabilization algorithms are of greater importance nowadays with the prevalence of hand-held devices which unavoidably produce videos with undesirable shaky motions. In this…

cs.CV2019★ 255 cited

FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation

Xiang Li, Tianhan Wei, Yau Pun Chen +2

Over the past few years, we have witnessed the success of deep learning in image recognition thanks to the availability of large-scale human-annotated datasets such as PASCAL VOC,…

cs.CV2019★ 9 cited

LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup

Qiao Gu, Guanzhi Wang, Mang Tik Chiu +2

We propose a local adversarial disentangling network (LADN) for facial makeup and de-makeup. Central to our method are multiple and overlapping local adversarial discriminators in…