activity
20192026
most citedDiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

39 citations · 104 across the 32 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2026

Quo Vadis, World Modeling?

Yu Yang, Xuemeng Yang, Licheng Wen +17

Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow, unsafe, and hard to paralleliz…

cs.CV2025

UR-Bench: A Benchmark for Multi-Hop Reasoning over Ultra-High-Resolution Images

Siqi Li, Xinyu Cai, Jianbiao Mei +7

Recent multimodal large language models (MLLMs) show strong capabilities in visual-language reasoning, yet their performance on ultra-high-resolution imagery remains largely unexpl…

cs.CV2025

Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Models

Jianbiao Mei, Yu Yang, Xuemeng Yang +4

End-to-end autonomous driving systems increasingly rely on vision-centric world models to understand and predict their environment. However, a common ineffectiveness in these model…

cs.CV2025

IWR-Bench: Can LVLMs reconstruct interactive webpage from a user interaction video?

Yang Chen, Minghao Liu, Yufan Shen +18

The webpage-to-code task requires models to understand visual representations of webpages and generate corresponding code. However, existing benchmarks primarily focus on static sc…

cs.CV2025

OmniCaptioner: One Captioner to Rule Them All

Yiting Lu, Jiakang Yuan, Zhen Li +17

We propose OmniCaptioner, a versatile visual captioning framework for generating fine-grained textual descriptions across a wide variety of visual domains. Unlike prior methods lim…

cs.CV2024★ 1 cited

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

Qingyun Li, Zhe Chen, Weiyun Wang +37

Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…

cs.CV2024★ 1 cited

OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving

Guohang Yan, Jiahao Pi, Jianfei Guo +14

With deep learning and computer vision technology development, autonomous driving provides new solutions to improve traffic safety and efficiency. The importance of building high-q…

cs.CV2023★ 21 cited

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

Licheng Wen, Xuemeng Yang, Daocheng Fu +15

The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven a…