From the 1 of 16 linked papers with an AI index.
16 papers
SimWAM: A Simple World Action Model for End-to-End Autonomous Driving
Zongchuang Zhao, Xin Zhou, Tianyang Xu +5
World-Action Models (WAMs) improve end-to-end autonomous driving by transferring video dynamics priors to action prediction, but existing methods incur costly test-time future imag…
ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation
Xiao Luo, Mingyang Du, Xin Zhou +5
The paper introduces ROAD, a framework that transfers semantic and structural knowledge from discriminative 3D foundation models into diffusion transformers for 3D shape generation…
SAM 2++: Tracking Anything at Any Granularity
Jiaming Zhang, Cheng Liang, Yichun Yang +7
Due to the varying granularity of target states across different tasks, most existing trackers are tailored to a single task, which specificity limits their generalization, prevent…
HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation
Xin Zhou, Dingkang Liang, Xiwu Chen +4
Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominantly focus on future scene gen…
Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models
Kaijin Chen, Dingkang Liang, Xin Zhou +4
Video world models have shown immense potential in simulating the physical world, yet existing memory mechanisms primarily treat environments as static canvases. When dynamic subje…
UniFuture: A 4D Driving World Model for Future Generation and Perception
Dingkang Liang, Dingyuan Zhang, Xin Zhou +7
We present UniFuture, a unified 4D Driving World Model designed to simulate the dynamic evolution of the 3D physical world. Unlike existing driving world models that focus solely o…