4 citations · 6 across the 20 of their papers we have counts for
5 papers · 1 filter
Benchmark Everything Everywhere All at Once
Shiyun Xiong, Dongming Wu, Peiwen Sun +5
Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit measures of performance. However, their construction is labor-intensiv…
Bridging Scene Generation and Planning: Driving with World Model via Unifying Vision and Motion Representation
Xingtai Gui, Meijie Zhang, Tianyi Yan +5
End-to-end autonomous driving aims to generate safe and plausible planning policies from raw sensor input. Driving world models have shown great potential in learning rich represen…
HanMoVLM: Large Vision-Language Models for Professional Artistic Painting Evaluation
Hongji Yang, Yucheng Zhou, Wencheng Han +3
While Large Vision-Language Models (VLMs) demonstrate impressive general visual capabilities, they remain artistically blind and unable to offer professional evaluation of artworks…
Towards Geometry-Aware and Motion-Guided Video Human Mesh Recovery
Hongjun Chen, Huan Zheng, Wencheng Han +1
Existing video-based 3D Human Mesh Recovery (HMR) methods often produce physically implausible results, stemming from their reliance on flawed intermediate 3D pose anchors and thei…
From Human Intention to Action Prediction: Intention-Driven End-to-End Autonomous Driving
Huan Zheng, Yucheng Zhou, Tianyi Yan +9
While end-to-end autonomous driving has achieved remarkable progress in geometric control, current systems remain constrained by a command-following paradigm that relies on simple…