24 citations · 106 across the 26 of their papers we have counts for
4 papers · 1 filter
Semantics-Depth-Symbiosis: Deeply Coupled Semi-Supervised Learning of Semantics and Depth
Nitin Bansal, Pan Ji, Junsong Yuan +1
Multi-task learning (MTL) paradigm focuses on jointly learning two or more tasks, aiming for significant improvement w.r.t model's generalizability, performance, and training/infer…
Strengthening Skeletal Action Recognizers via Leveraging Temporal Patterns
Zhenyue Qin, Pan Ji, Dongwoo Kim +3
Skeleton sequences are compact and lightweight. Numerous skeleton-based action recognizers have been proposed to classify human behaviors. In this work, we aim to incorporate compo…
Representation-Centric Survey of Supervised Skeletal Action Recognition and the New Benchmark
Yang Liu, Jiyao Yang, Madhawa Perera +8
3D skeletal action recognition has emerged as a powerful alternative to traditional RGB and depth-based approaches, offering robustness to environmental variations, computational e…
Deformable VisTR: Spatio temporal deformable attention for video instance segmentation
Sudhir Yarram, Jialian Wu, Pan Ji +2
Video instance segmentation (VIS) task requires classifying, segmenting, and tracking object instances over all frames in a video clip. Recently, VisTR has been proposed as end-to-…