53 citations · 321 across the 50 of their papers we have counts for
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Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos
Yu Cheng, Bo Wang, Bo Yang +1
Despite the recent progress, 3D multi-person pose estimation from monocular videos is still challenging due to the commonly encountered problem of missing information caused by occ…
Multi-Scale Networks for 3D Human Pose Estimation with Inference Stage Optimization
Cheng Yu, Bo Wang, Bo Yang +1
Estimating 3D human poses from a monocular video is still a challenging task. Many existing methods' performance drops when the target person is occluded by other objects, or the m…
Object Tracking Using Spatio-Temporal Future Prediction
Yuan Liu, Ruoteng Li, Robby T. Tan +2
Occlusion is a long-standing problem that causes many modern tracking methods to be erroneous. In this paper, we address the occlusion problem by exploiting the current and future…
Estimation of Camera Response Function using Prediction Consistency and Gradual Refinement with an Extension to Deep Learning
Aashish Sharma, Robby T. Tan, Loong-Fah Cheong
Most existing methods for CRF estimation from a single image fail to handle general real images. For instance, EdgeCRF based on colour patches extracted from edges works effectivel…
3D Human Pose Estimation using Spatio-Temporal Networks with Explicit Occlusion Training
Yu Cheng, Bo Yang, Bo Wang +1
Estimating 3D poses from a monocular video is still a challenging task, despite the significant progress that has been made in recent years. Generally, the performance of existing…
Optical Flow in Dense Foggy Scenes using Semi-Supervised Learning
Wending Yan, Aashish Sharma, Robby T. Tan
In dense foggy scenes, existing optical flow methods are erroneous. This is due to the degradation caused by dense fog particles that break the optical flow basic assumptions such…