203 citations · 556 across the 17 of their papers we have counts for
29 papers · 1 filter
Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling
Yulin Liu, Haoran Liu, Yingda Yin +3
Normalizing flows (NFs) provide a powerful tool to construct an expressive distribution by a sequence of trackable transformations of a base distribution and form a probabilistic m…
Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images
Jiatao Gu, Qingzhe Gao, Shuangfei Zhai +3
Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulti…
SinGRAV: Learning a Generative Radiance Volume from a Single Natural Scene
Yujie Wang, Xuelin Chen, Baoquan Chen
We present a 3D generative model for general natural scenes. Lacking necessary volumes of 3D data characterizing the target scene, we propose to learn from a single scene. Our key…
Multi-Robot Active Mapping via Neural Bipartite Graph Matching
Kai Ye, Siyan Dong, Qingnan Fan +5
We study the problem of multi-robot active mapping, which aims for complete scene map construction in minimum time steps. The key to this problem lies in the goal position estimati…
FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filtering
Yingda Yin, Yingcheng Cai, He Wang +1
Estimating the 3DoF rotation from a single RGB image is an important yet challenging problem. Recent works achieve good performance relying on a large amount of expensive-to-obtain…
Self-Conditioned Generative Adversarial Networks for Image Editing
Yunzhe Liu, Rinon Gal, Amit H. Bermano +2
Generative Adversarial Networks (GANs) are susceptible to bias, learned from either the unbalanced data, or through mode collapse. The networks focus on the core of the data distri…