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cs.CV2026

SimWAM: A Simple World Action Model for End-to-End Autonomous Driving

Zongchuang Zhao, Xin Zhou, Tianyang Xu +6

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…

cs.CV2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

Xiao Luo, Mingyang Du, Xin Zhou +5

High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typically requires learning geometr…

cs.CV2026

When Numbers Speak: Aligning Textual Numerals and Visual Instances in Text-to-Video Diffusion Models

Zhengyang Sun, Yu Chen, Xin Zhou +4

Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a prompt. We introduce NUMINA…

cs.CV2026

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…

cs.CV2025

FVAR: Visual Autoregressive Modeling via Next Focus Prediction

Xiaofan Li, Chenming Wu, Yanpeng Sun +6

Visual autoregressive models achieve remarkable generation quality through next-scale predictions across multi-scale token pyramids. However, the conventional method uses uniform s…

cs.CV2025

Video4Edit: Viewing Image Editing as a Degenerate Temporal Process

Xiaofan Li, Yanpeng Sun, Chenming Wu +5

We observe that recent advances in multimodal foundation models have propelled instruction-driven image generation and editing into a genuinely cross-modal, cooperative regime. Nev…