17 citations · 17 across the 21 of their papers we have counts for
10 papers · 1 filter
CoDrive: Cross-Vehicle World-Consistent Video Generation with Precise Trajectory Control for Cooperative Driving
Yu Meng, Baining Zhao, Junta Wu +10
Real-world driving is inherently multi-agent, yet most existing driving world models generate observations from a single ego vehicle. Independently extending them to multiple vehic…
EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning
Pengtao Ma, Ziliang Zhou, Ciyu Ruan +7
First-person dynamic spatial reasoning requires models to track continuous motion and precise geometric structure, but the quadratic attention cost of Transformer-based Video-LLMs…
iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework
Jianjie Fang, Yingshan Lei, Qin Wan +8
Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable environments for perception, re…
AirCopBench: A Benchmark for Multi-drone Collaborative Embodied Perception and Reasoning
Jirong Zha, Yuxuan Fan, Tianyu Zhang +4
Multimodal Large Language Models (MLLMs) have shown promise in single-agent vision tasks, yet benchmarks for evaluating multi-agent collaborative perception remain scarce. This gap…
EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent
Jiaao Li, Kaiyuan Li, Chen Gao +2
Egomotion videos are first-person recordings where the view changes continuously due to the agent's movement. As they serve as the primary visual input for embodied AI agents, maki…
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking
Jirong Zha, Yuxuan Fan, Kai Li +4
State estimation is challenging for 3D object tracking with high maneuverability, as the target's state transition function changes rapidly, irregularly, and is unknown to the esti…
How to Enable LLM with 3D Capacity? A Survey of Spatial Reasoning in LLM
Jirong Zha, Yuxuan Fan, Xiao Yang +2
3D spatial understanding is essential in real-world applications such as robotics, autonomous vehicles, virtual reality, and medical imaging. Recently, Large Language Models (LLMs)…
The Point, the Vision and the Text: Does Point Cloud Boost Spatial Reasoning of Large Language Models? A Bias-Controlled Study
Weichen Zhang, Ruiying Peng, Xin Zeng +9
3D Large Language Models (LLMs) leveraging spatial information in point clouds for 3D spatial reasoning attract great attention. Despite some promising results, the advantages of p…
UrbanVideo-Bench: Benchmarking Vision-Language Models on Embodied Intelligence with Video Data in Urban Spaces
Baining Zhao, Jianjie Fang, Zichao Dai +8
Large multimodal models exhibit remarkable intelligence, yet their embodied cognitive abilities during motion in open-ended urban 3D space remain to be explored. We introduce a ben…
Open3D-VQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open Space
Weichen Zhang, Zile Zhou, Xin Zeng +7
Spatial reasoning is a fundamental capability of multimodal large language models (MLLMs), yet their performance in open aerial environments remains underexplored. In this work, we…