3 citations · 7 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection
Ming Nie, Yujing Xue, Chunwei Wang +7
Recently, polar-based representation has shown promising properties in perceptual tasks. In addition to Cartesian-based approaches, which separate point clouds unevenly, representi…
SUIT: Learning Significance-guided Information for 3D Temporal Detection
Zheyuan Zhou, Jiachen Lu, Yihan Zeng +2
3D object detection from LiDAR point cloud is of critical importance for autonomous driving and robotics. While sequential point cloud has the potential to enhance 3D perception th…
Learning Ego 3D Representation as Ray Tracing
Jiachen Lu, Zheyuan Zhou, Xiatian Zhu +2
A self-driving perception model aims to extract 3D semantic representations from multiple cameras collectively into the bird's-eye-view (BEV) coordinate frame of the ego car in ord…