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20242026
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cs.CV2026

Overcoming Statistical Bias in Action-Controllable World Models

Yuhong Shi, Zhenhao Chu, Jie Wei +3

Action-conditioned world models aim to predict how visual environments evolve under an agent's actions. Yet future frames are often highly predictable from visual inertia and recur…

cs.CV2026

The Essence of Balance for Self-Improving Agents in Vision-and-Language Navigation

Zhen Liu, Yuhan Liu, Jinjun Wang +3

In vision-and-language navigation (VLN), self-improvement from policy-induced experience, using only standard VLN action supervision, critically depends on balancing behavioral div…

cs.CV2026

Instruction-as-State: Environment-Guided and State-Conditioned Semantic Understanding for Embodied Navigation

Zhen Liu, Yuhan Liu, Jinjun Wang +3

Vision-and-Language Navigation requires agents to follow natural-language instructions in visually changing environments. A central challenge is the dynamic entanglement between la…

cs.CV2025

DAMap: Distance-aware MapNet for High Quality HD Map Construction

Jinpeng Dong, Chen Li, Yutong Lin +3

Predicting High-definition (HD) map elements with high quality (high classification and localization scores) is crucial to the safety of autonomous driving vehicles. However, curre…

cs.CV2025

StructVPR++: Distill Structural and Semantic Knowledge with Weighting Samples for Visual Place Recognition

Yanqing Shen, Sanping Zhou, Jingwen Fu +3

Visual place recognition is a challenging task for autonomous driving and robotics, which is usually considered as an image retrieval problem. A commonly used two-stage strategy in…

cs.CV2025

REGNav: Room Expert Guided Image-Goal Navigation

Pengna Li, Kangyi Wu, Jingwen Fu +1

Image-goal navigation aims to steer an agent towards the goal location specified by an image. Most prior methods tackle this task by learning a navigation policy, which extracts vi…

cs.CV2024

PromptTA: Prompt-driven Text Adapter for Source-free Domain Generalization

Haoran Zhang, Shuanghao Bai, Wanqi Zhou +2

Source-free domain generalization (SFDG) tackles the challenge of adapting models to unseen target domains without access to source domain data. To deal with this challenging task,…