183 citations · 290 across the 6 of their papers we have counts for
8 papers
Multi-Object Manipulation via Object-Centric Neural Scattering Functions
Stephen Tian, Yancheng Cai, Hong-Xing Yu +5
Learned visual dynamics models have proven effective for robotic manipulation tasks. Yet, it remains unclear how best to represent scenes involving multi-object interactions. Curre…
Neural Radiance Flow for 4D View Synthesis and Video Processing
Yilun Du, Yinan Zhang, Hong-Xing Yu +2
We present a method, Neural Radiance Flow (NeRFlow),to learn a 4D spatial-temporal representation of a dynamic scene from a set of RGB images. Key to our approach is the use of a n…
Weakly supervised discriminative feature learning with state information for person identification
Hong-Xing Yu, Wei-Shi Zheng
Unsupervised learning of identity-discriminative visual feature is appealing in real-world tasks where manual labelling is costly. However, the images of an identity can be visuall…
DSRGAN: Explicitly Learning Disentangled Representation of Underlying Structure and Rendering for Image Generation without Tuple Supervision
Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
We focus on explicitly learning disentangled representation for natural image generation, where the underlying spatial structure and the rendering on the structure can be independe…
Unsupervised Person Re-identification by Soft Multilabel Learning
Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu +3
Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models,…
Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding
Hong-Xing Yu, Ancong Wu, Wei-Shi Zheng
Person re-identification (Re-ID) aims to match identities across non-overlapping camera views. Researchers have proposed many supervised Re-ID models which require quantities of cr…