3 citations · 5 across the 11 of their papers we have counts for
12 papers
Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization
Ming Nie, Chunwei Wang, Jianhua Han +2
Unified vision-language models have made significant progress in multimodal understanding and generation, yet they largely fall short in producing multimodal interleaved outputs, w…
SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM
Ming Nie, Dan Ding, Chunwei Wang +4
Large language models (LLMs) have demonstrated exceptional capabilities in text understanding, which has paved the way for their expansion into video LLMs (Vid-LLMs) to analyze vid…
KFFocus: Highlighting Keyframes for Enhanced Video Understanding
Ming Nie, Chunwei Wang, Hang Xu +1
Recently, with the emergence of large language models, multimodal LLMs have demonstrated exceptional capabilities in image and video modalities. Despite advancements in video compr…
From Flatland to Space: Teaching Vision-Language Models to Perceive and Reason in 3D
Jiahui Zhang, Yurui Chen, Yanpeng Zhou +10
Recent advances in LVLMs have improved vision-language understanding, but they still struggle with spatial perception, limiting their ability to reason about complex 3D scenes. Unl…
FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise
Yunlong Yuan, Yuanfan Guo, Chunwei Wang +3
Text-driven video generation has advanced significantly due to developments in diffusion models. Beyond the training and sampling phases, recent studies have investigated noise pri…
Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising
Yunlong Yuan, Yuanfan Guo, Chunwei Wang +2
Recent advances in diffusion models have greatly improved text-driven video generation. However, training models for long video generation demands significant computational power a…
LaneCorrect: Self-supervised Lane Detection
Ming Nie, Xinyue Cai, Hang Xu +1
Lane detection has evolved highly functional autonomous driving system to understand driving scenes even under complex environments. In this paper, we work towards developing a gen…
OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation
Haochen Jiang, Yueming Xu, Yihan Zeng +4
3D reconstruction has been widely used in autonomous navigation fields of mobile robotics. However, the former research can only provide the basic geometry structure without the ca…
From Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs
Yulong Liu, Yunlong Yuan, Chunwei Wang +5
The distinction between humans and animals lies in the unique ability of humans to use and create tools. Tools empower humans to overcome physiological limitations, fostering the c…
LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement
Renyuan Peng, Xinyue Cai, Hang Xu +4
Understanding road structures is crucial for autonomous driving. Intricate road structures are often depicted using lane graphs, which include centerline curves and connections for…
Translating Images to Road Network: A Sequence-to-Sequence Perspective
Jiachen Lu, Ming Nie, Bozhou Zhang +6
The extraction of road network is essential for the generation of high-definition maps since it enables the precise localization of road landmarks and their interconnections. Howev…
Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
Ming Nie, Renyuan Peng, Chunwei Wang +4
Large vision-language models (VLMs) have garnered increasing interest in autonomous driving areas, due to their advanced capabilities in complex reasoning tasks essential for highl…