Search Results for author: Xiao Bian

Found 13 papers, 4 papers with code

Label Budget Allocation in Multi-Task Learning

no code implementations24 Aug 2023 Ximeng Sun, Kihyuk Sohn, Kate Saenko, Clayton Mellina, Xiao Bian

How should the label budget (i. e. the amount of money spent on labeling) be allocated among different tasks to achieve optimal multi-task performance?

Multi-Task Learning

Detection and Tracking Meet Drones Challenge

2 code implementations16 Jan 2020 Pengfei Zhu, Longyin Wen, Dawei Du, Xiao Bian, Heng Fan, QinGhua Hu, Haibin Ling

We provide a large-scale drone captured dataset, VisDrone, which includes four tracks, i. e., (1) image object detection, (2) video object detection, (3) single object tracking, and (4) multi-object tracking.

Multi-Object Tracking Object +2

Learning Non-Uniform Hypergraph for Multi-Object Tracking

no code implementations10 Dec 2018 Longyin Wen, Dawei Du, Shengkun Li, Xiao Bian, Siwei Lyu

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 less effective in handling complex scenarios.

Multi-Object Tracking Object

Evolvement Constrained Adversarial Learning for Video Style Transfer

no code implementations6 Nov 2018 Wenbo Li, Longyin Wen, Xiao Bian, Siwei Lyu

Video style transfer is a useful component for applications such as augmented reality, non-photorealistic rendering, and interactive games.

Generative Adversarial Network Optical Flow Estimation +2

Robust Adversarial Perturbation on Deep Proposal-based Models

no code implementations16 Sep 2018 Yuezun Li, Daniel Tian, Ming-Ching Chang, Xiao Bian, Siwei Lyu

Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms.

Instance Segmentation Region Proposal +2

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

no code implementations16 Sep 2018 Yuezun Li, Xiao Bian, Ming-Ching Chang, Siwei Lyu

In this paper, we focus on exploring the vulnerability of the Single Shot Module (SSM) commonly used in recent object detectors, by adding small perturbations to patches in the background outside the object.

Object Region Proposal

Occlusion-aware R-CNN: Detecting Pedestrians in a Crowd

no code implementations ECCV 2018 Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, Stan Z. Li

Pedestrian detection in crowded scenes is a challenging problem since the pedestrians often gather together and occlude each other.

Ranked #10 on Pedestrian Detection on Caltech (using extra training data)

Pedestrian Detection

Vision Meets Drones: A Challenge

no code implementations20 Apr 2018 Pengfei Zhu, Longyin Wen, Xiao Bian, Haibin Ling, QinGhua Hu

In this paper we present a large-scale visual object detection and tracking benchmark, named VisDrone2018, aiming at advancing visual understanding tasks on the drone platform.

Multi-Object Tracking Object +2

Single-Shot Refinement Neural Network for Object Detection

12 code implementations CVPR 2018 Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, Stan Z. Li

For object detection, the two-stage approach (e. g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e. g., SSD) has the advantage of high efficiency.

Object object-detection +1

Robust Subspace Recovery via Bi-Sparsity Pursuit

no code implementations31 Mar 2014 Xiao Bian, Hamid Krim

Successful applications of sparse models in computer vision and machine learning imply that in many real-world applications, high dimensional data is distributed in a union of low dimensional subspaces.

BIG-bench Machine Learning

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