activity
20192022
most citedLearning Anthropometry from Rendered Humans

12 citations · 25 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20228 cited

RGBD Object Tracking: An In-depth Review

Jinyu Yang, Zhe Li, Song Yan +4

RGBD object tracking is gaining momentum in computer vision research thanks to the development of depth sensors. Although numerous RGBD trackers have been proposed with promising p…

cs.CV20212 cited

Depth-only Object Tracking

Song Yan, Jinyu Yang, Ales Leonardis +1

Depth (D) indicates occlusion and is less sensitive to illumination changes, which make depth attractive modality for Visual Object Tracking (VOT). Depth is used in RGBD object tra…

cs.CV2021

DepthTrack : Unveiling the Power of RGBD Tracking

Song Yan, Jinyu Yang, Jani Käpylä +3

RGBD (RGB plus depth) object tracking is gaining momentum as RGBD sensors have become popular in many application fields such as robotics.However, the best RGBD trackers are extens…

cs.CV202112 cited

Learning Anthropometry from Rendered Humans

Song Yan, Joni-Kristian Kämäräinen

Accurate estimation of anthropometric body measurements from RGB images has many potential applications in industrial design, online clothing, medical diagnosis and ergonomics. Res…

cs.CV20191 cited

Anthropometric clothing measurements from 3D body scans

Song Yan, Johan Wirta, Joni-Kristian Kämäräinen

We propose a full processing pipeline to acquire anthropometric measurements from 3D measurements. The first stage of our pipeline is a commercial point cloud scanner. In the secon…

cs.CV20192 cited

Flash Lightens Gray Pixels

Yanlin Qian, Song Yan, Joni-Kristian Kämäräinen +1

In the real world, a scene is usually cast by multiple illuminants and herein we address the problem of spatial illumination estimation. Our solution is based on detecting gray pix…