24 citations · 26 across the 6 of their papers we have counts for
6 papers
S2GO: Streaming Sparse Gaussian Occupancy Prediction
Jinhyung Park, Yihan Hu, Chensheng Peng +3
Despite the demonstrated efficiency and performance of sparse query-based representations for perception, state-of-the-art 3D occupancy prediction methods still rely on voxel-based…
X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios
Yichen Xie, Chenfeng Xu, Chensheng Peng +6
Recent advancements have exploited diffusion models for the synthesis of either LiDAR point clouds or camera image data in driving scenarios. Despite their success in modeling sing…
CompGS: Unleashing 2D Compositionality for Compositional Text-to-3D via Dynamically Optimizing 3D Gaussians
Chongjian Ge, Chenfeng Xu, Yuanfeng Ji +6
Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, gener…
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Yixiao Wang, Chen Tang, Lingfeng Sun +8
Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high c…
PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search
Chensheng Peng, Zhaoyu Zeng, Jinling Gao +5
Multiple object tracking is a critical task in autonomous driving. Existing works primarily focus on the heuristic design of neural networks to obtain high accuracy. As tracking ac…
DELFlow: Dense Efficient Learning of Scene Flow for Large-Scale Point Clouds
Chensheng Peng, Guangming Wang, Xian Wan Lo +5
Point clouds are naturally sparse, while image pixels are dense. The inconsistency limits feature fusion from both modalities for point-wise scene flow estimation. Previous methods…