3 citations · 5 across the 7 of their papers we have counts for
7 papers
Distribution-Aligned Diffusion for Human Mesh Recovery
Lin Geng Foo, Jia Gong, Hossein Rahmani +1
Recovering a 3D human mesh from a single RGB image is a challenging task due to depth ambiguity and self-occlusion, resulting in a high degree of uncertainty. Meanwhile, diffusion…
Token Boosting for Robust Self-Supervised Visual Transformer Pre-training
Tianjiao Li, Lin Geng Foo, Ping Hu +4
Learning with large-scale unlabeled data has become a powerful tool for pre-training Visual Transformers (VTs). However, prior works tend to overlook that, in real-world scenarios,…
System-status-aware Adaptive Network for Online Streaming Video Understanding
Lin Geng Foo, Jia Gong, Zhipeng Fan +1
Recent years have witnessed great progress in deep neural networks for real-time applications. However, most existing works do not explicitly consider the general case where the de…
GradMDM: Adversarial Attack on Dynamic Networks
Jianhong Pan, Lin Geng Foo, Qichen Zheng +4
Dynamic neural networks can greatly reduce computation redundancy without compromising accuracy by adapting their structures based on the input. In this paper, we explore the robus…
Progressive Channel-Shrinking Network
Jianhong Pan, Siyuan Yang, Lin Geng Foo +4
Currently, salience-based channel pruning makes continuous breakthroughs in network compression. In the realization, the salience mechanism is used as a metric of channel salience…
Dynamic Spatio-Temporal Specialization Learning for Fine-Grained Action Recognition
Tianjiao Li, Lin Geng Foo, Qiuhong Ke +4
The goal of fine-grained action recognition is to successfully discriminate between action categories with subtle differences. To tackle this, we derive inspiration from the human…