2 citations · 2 across the 7 of their papers we have counts for
9 papers
Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model
Liming Lu, Xianzheng Ma, Wenkun He +14
Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical principles. Existing approac…
The 10th AI City Challenge
Zheng Tang, Shuo Wang, David C. Anastasiu +34
The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical AI. Since its 2017 start with v…
From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning
Han Zhang, Yilin Zhao, Zaid Pervaiz Bhat +5
Detecting a traffic anomaly does not establish whether a video-language model can explain what happened, localize it in time, or identify its causes. We introduce TAR (Traffic Anom…
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
Action Images: End-to-End Policy Learning via Multiview Video Generation
Haoyu Zhen, Zixian Gao, Qiao Sun +7
World action models (WAMs) have emerged as a promising direction for robot policy learning, as they can leverage powerful video backbones to model the future states. However, exist…
A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting
Junlin Li, Xinhao Song, Siqi Wang +2
Text-driven motion editing and intra-structural retargeting, where skeletons share topology but may differ in bone lengths and rest pose, are traditionally handled by fragmented pi…
3D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing
Haoyu Zhen, Xiaolong Li, Yilin Zhao +5
Large Language Models (LLMs) and Vision Language Models (VLMs) have shown impressive reasoning abilities, yet they struggle with spatial understanding and layout consistency when p…
The 9th AI City Challenge
Zheng Tang, Shuo Wang, David C. Anastasiu +25
The ninth AI City Challenge continues to advance real-world applications of computer vision and AI in transportation, industrial automation, and public safety. The 2025 edition fea…
Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models
Zhiqi Li, Guo Chen, Shilong Liu +24
Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models. However, most…