2 citations · 6 across the 24 of their papers we have counts for
7 papers · 1 filter
DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT
Xiaotao Hu, Mingkai Jia, Xiaoyang Guo +3
Recent successes in autoregressive (AR) generation models, such as the GPT series in natural language processing, have motivated efforts to replicate this success in visual tasks.…
Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration
Junyuan Deng, Wei Yin, Xiaoyang Guo +5
In this paper, we present DM-Calib, a diffusion-based approach for estimating pinhole camera intrinsic parameters from a single input image. Monocular camera calibration is essenti…
Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
Bo Jiang, Shaoyu Chen, Bencheng Liao +6
End-to-end autonomous driving demonstrates strong planning capabilities with large-scale data but still struggles in complex, rare scenarios due to limited commonsense. In contrast…
DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model
Songen Gu, Wei Yin, Bu Jin +5
We propose DOME, a diffusion-based world model that predicts future occupancy frames based on past occupancy observations. The ability of this world model to capture the evolution…
ComDrive: Comfort-Oriented End-to-End Autonomous Driving
Junming Wang, Xingyu Zhang, Zebin Xing +7
We propose ComDrive: the first comfort-oriented end-to-end autonomous driving system to generate temporally consistent and comfortable trajectories. Recent studies have demonstrate…
OccRWKV: Rethinking Efficient 3D Semantic Occupancy Prediction with Linear Complexity
Junming Wang, Wei Yin, Xiaoxiao Long +4
3D semantic occupancy prediction networks have demonstrated remarkable capabilities in reconstructing the geometric and semantic structure of 3D scenes, providing crucial informati…
Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
Jing He, Haodong Li, Wei Yin +6
Leveraging the visual priors of pre-trained text-to-image diffusion models offers a promising solution to enhance zero-shot generalization in dense prediction tasks. However, exist…