activity
20182020
most citedLaSOT: A High-quality Large-scale Single Object Tracking Benchmark

14 citations · 25 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV202014 cited

LaSOT: A High-quality Large-scale Single Object Tracking Benchmark

Heng Fan, Hexin Bai, Liting Lin +11

Despite great recent advances in visual tracking, its further development, including both algorithm design and evaluation, is limited due to lack of dedicated large-scale benchmark…

cs.CV20193 cited

Dually Supervised Feature Pyramid for Object Detection and Segmentation

Fan Yang, Cheng Lu, Yandong Guo +2

Feature pyramid architecture has been broadly adopted in object detection and segmentation to deal with multi-scale problem. However, in this paper we show that the capacity of the…

cs.CV20198 cited

TracKlinic: Diagnosis of Challenge Factors in Visual Tracking

Heng Fan, Fan Yang, Peng Chu +2

Generic visual tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracking algorithm, and whe…

cs.CV2019

Clustered Object Detection in Aerial Images

Fan Yang, Heng Fan, Peng Chu +2

Detecting objects in aerial images is challenging for at least two reasons: (1) target objects like pedestrians are very small in pixels, making them hardly distinguished from surr…

cs.CV2018

LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking

Heng Fan, Liting Lin, Fan Yang +7

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame…

cs.CV2018

Privacy-Protective-GAN for Face De-identification

Yifan Wu, Fan Yang, Haibin Ling

Face de-identification has become increasingly important as the image sources are explosively growing and easily accessible. The advance of new face recognition techniques also ari…