104 citations · 222 across the 24 of their papers we have counts for
8 papers · 1 filter
NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstruction
Yiming Wang, Qin Han, Marc Habermann +3
Recent methods for neural surface representation and rendering, for example NeuS, have demonstrated the remarkably high-quality reconstruction of static scenes. However, the traini…
Cross-view Graph Contrastive Representation Learning on Partially Aligned Multi-view Data
Yiming Wang, Dongxia Chang, Zhiqiang Fu +2
Multi-view representation learning has developed rapidly over the past decades and has been applied in many fields. However, most previous works assumed that each view is complete…
Leveraging commonsense for object localisation in partial scenes
Francesco Giuliari, Geri Skenderi, Marco Cristani +2
We propose an end-to-end solution to address the problem of object localisation in partial scenes, where we aim to estimate the position of an object in an unknown area given only…
Oracle-guided Contrastive Clustering
Mengdie Wang, Liyuan Shang, Suyun Zhao +4
Deep clustering aims to learn a clustering representation through deep architectures. Most of the existing methods usually conduct clustering with the unique goal of maximizing clu…
Neural Novel Actor: Learning a Generalized Animatable Neural Representation for Human Actors
Yiming Wang, Qingzhe Gao, Libin Liu +3
We propose a new method for learning a generalized animatable neural human representation from a sparse set of multi-view imagery of multiple persons. The learned representation ca…
PI-Trans: Parallel-ConvMLP and Implicit-Transformation Based GAN for Cross-View Image Translation
Bin Ren, Hao Tang, Yiming Wang +3
For semantic-guided cross-view image translation, it is crucial to learn where to sample pixels from the source view image and where to reallocate them guided by the target view se…