8 citations · 32 across the 9 of their papers we have counts for
12 papers · 1 filter
Multi-Frequency-Aware Patch Adversarial Learning for Neural Point Cloud Rendering
Jay Karhade, Haiyue Zhu, Ka-Shing Chung +3
We present a neural point cloud rendering pipeline through a novel multi-frequency-aware patch adversarial learning framework. The proposed approach aims to improve the rendering r…
Voxel-based Network for Shape Completion by Leveraging Edge Generation
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Deep learning technique has yielded significant improvements in point cloud completion with the aim of completing missing object shapes from partial inputs. However, most existing…
A Stronger Baseline for Ego-Centric Action Detection
Zhiwu Qing, Ziyuan Huang, Xiang Wang +7
This technical report analyzes an egocentric video action detection method we used in the 2021 EPIC-KITCHENS-100 competition hosted in CVPR2021 Workshop. The goal of our task is to…
Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition
Ziyuan Huang, Zhiwu Qing, Xiang Wang +7
With the recent surge in the research of vision transformers, they have demonstrated remarkable potential for various challenging computer vision applications, such as image recogn…
Self-supervised Motion Learning from Static Images
Ziyuan Huang, Shiwei Zhang, Jianwen Jiang +3
Motions are reflected in videos as the movement of pixels, and actions are essentially patterns of inconsistent motions between the foreground and the background. To well distingui…
Cascaded Refinement Network for Point Cloud Completion with Self-supervision
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Point clouds are often sparse and incomplete, which imposes difficulties for real-world applications. Existing shape completion methods tend to generate rough shapes without fine-g…