1 citations · 1 across the 10 of their papers we have counts for
10 papers
Bridging 3D Gaussians and Semantic Occupancy for Comprehensive Open-Vocabulary Scene Understanding from Unposed Images
Hu Zhu, Bohan Li, Xianda Guo +5
Comprehensive 3D scene understanding from sparse, unposed images requires a model to recover renderable geometry, open-vocabulary semantics, and free/occupied 3D space without rely…
Interpretable Single-View 3D Gaussian Splatting using Unsupervised Hierarchical Disentangled Representation Learning
Yuyang Zhang, Baao Xie, Hu Zhu +4
Gaussian Splatting (GS) has recently marked a significant advancement in 3D reconstruction, delivering both rapid rendering and high-quality results. However, existing 3DGS methods…
OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation
Bohan Li, Xin Jin, Jianan Wang +8
Recent diffusion models have demonstrated remarkable performance in both 3D scene generation and perception tasks. Nevertheless, existing methods typically separate these two proce…
Hierarchical Context Alignment with Disentangled Geometric and Temporal Modeling for Semantic Occupancy Prediction
Bohan Li, Jiajun Deng, Yasheng Sun +3
Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding complex 3D scenes from limited 2D image observations. Existing SOP methods typically aggregate cont…
UniScene: Unified Occupancy-centric Driving Scene Generation
Bohan Li, Jiazhe Guo, Hongsi Liu +14
Generating high-fidelity, controllable, and annotated training data is critical for autonomous driving. Existing methods typically generate a single data form directly from a coars…
Hierarchical Temporal Context Learning for Camera-based Semantic Scene Completion
Bohan Li, Jiajun Deng, Wenyao Zhang +4
Camera-based 3D semantic scene completion (SSC) is pivotal for predicting complicated 3D layouts with limited 2D image observations. The existing mainstream solutions generally lev…
One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception
Bohan Li, Yasheng Sun, Jingxin Dong +4
Numerous studies have investigated the pivotal role of reliable 3D volume representation in scene perception tasks, such as multi-view stereo (MVS) and semantic scene completion (S…
Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
Qi Wang, Junming Yang, Yunbo Wang +3
Training offline RL models using visual inputs poses two significant challenges, i.e., the overfitting problem in representation learning and the overestimation bias for expected f…
NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigation
Baao Xie, Bohan Li, Zequn Zhang +4
3D representation disentanglement aims to identify, decompose, and manipulate the underlying explanatory factors of 3D data, which helps AI fundamentally understand our 3D world. T…
ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generation
Liang Xu, Ziyang Song, Dongliang Wang +9
We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions. Ou…