activity
20172020
most citedSingle-Shot Refinement Neural Network for Object Detection

112 citations · 125 across the 2 of their papers we have counts for

collaborators

9 papers

cs.CV2020

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation

Yuliang Zou, Zizhao Zhang, Han Zhang +4

Recent advances in semi-supervised learning (SSL) demonstrate that a combination of consistency regularization and pseudo-labeling can effectively improve image classification accu…

cs.CV202013 cited

Feature Space Augmentation for Long-Tailed Data

Peng Chu, Xiao Bian, Shaopeng Liu +1

Real-world data often follow a long-tailed distribution as the frequency of each class is typically different. For example, a dataset can have a large number of under-represented c…

cs.CV2018

Learning Non-Uniform Hypergraph for Multi-Object Tracking

Longyin Wen, Dawei Du, Shengkun Li +2

The majority of Multi-Object Tracking (MOT) algorithms based on the tracking-by-detection scheme do not use higher order dependencies among objects or tracklets, which makes them l…

cs.CV2018

Evolvement Constrained Adversarial Learning for Video Style Transfer

Wenbo Li, Longyin Wen, Xiao Bian +1

Video style transfer is a useful component for applications such as augmented reality, non-photorealistic rendering, and interactive games. Many existing methods use optical flow t…

cs.CV2018

Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background Patches

Yuezun Li, Xiao Bian, Ming-ching Chang +1

Recent works succeeded to generate adversarial perturbations on the entire image or the object of interests to corrupt CNN based object detectors. In this paper, we focus on explor…

cs.CV2018

Robust Adversarial Perturbation on Deep Proposal-based Models

Yuezun Li, Daniel Tian, Ming-Ching Chang +2

Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms. In this paper, we describe a robust adversarial perturbation (R-AP) met…