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20232026
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8 papers · 1 filter

cs.CV2026

MORE: Learning Motion-Oriented Registers for Driving World Models and Planning

Yingdong Gu, Haoyu Wang, Shaocheng Yan +9

By predicting future states, latent world models provide rich self-supervision for end-to-end driving, but often inherit dense features from pretrained visual encoders as their wor…

cs.SD2026

Commanding at the Speed of Sound: Audio-Centric Referring Expression Segmentation for Aerial Scenes

Fan Liu, Ziyun Chen, Yijun Wang +6

Referring expression segmentation (RES) aims to localize targets at the pixel level guided by human instructions. However, current models predominantly follow a text-centric paradi…

cs.CV2026

DroneWAM: Efficient World Action Model for Drone Visual Navigation

Liang Yao, Fan Liu, Hongbo Lu +5

World-action models give visual navigation agents a way to anticipate how candidate actions will change future observations and to act from the predicted consequences. For drones,…

cs.CV2026

RISE: Adaptive Imagination for World Action Models

Hongbo Lu, Liang Yao, Chenghao He +5

World Action Models (WAMs) improve planning by incorporating future world evolution into action generation, yet existing methods allocate a fixed imagination budget to every scene.…

cs.CV2026

The DAWN of World-Action Interactive Models

Hongbo Lu, Liang Yao, Chenghao He +6

A plausible scene evolution depends on the maneuver being considered, while a good maneuver depends on how the scene may evolve. Existing World Action Models (WAMs) largely miss th…

cs.CV2026

VisionNVS: Self-Supervised Inpainting for Novel View Synthesis under the Virtual-Shift Paradigm

Hongbo Lu, Liang Yao, Chenghao He +4

A fundamental bottleneck in Novel View Synthesis (NVS) for autonomous driving is the inherent supervision gap on novel trajectories: models are tasked with synthesizing unseen view…

cs.CV2026

Clinical Cognition Alignment for Gastrointestinal Diagnosis with Multimodal LLMs

Huan Zheng, Yucheng Zhou, Tianyi Yan +6

Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastrointestinal endoscopy is currently hin…

cs.CV2026

WildSVG: Towards Reliable SVG Generation Under Real-Word Conditions

Marco Terral, Haotian Zhang, Tianyang Zhang +8

We introduce the task of SVG extraction, which consists in translating specific visual inputs from an image into scalable vector graphics. Existing multimodal models achieve strong…