6 accepted papers
Autonomous navigation of ground robots in unstructured 3D environments remains a fundamental challenge, as it requires accommodating dynamic obstacles, non-planar ground, and multi-story structures within a unified framework. In this paper, we propose a versatile navigation framework named FineNav. …
Vision-language-action models exhibit an inherent trade-off in action chunk length (``horizon''): longer horizons improve global foresight but degrade fine-grained local control, while shorter ones yield the opposite. To mitigate the trade-off, we propose a $\textbf{mixture of horizons (MoH)}$ strat…
Portrait pose transfer (PPT) requires generative models to preserve fine-grained identity details while following complex pose and layout modification instructions. Existing methods often struggle with extensive data annotation requirements or employ optimization objectives that are suboptimal for a…
As social media platforms proliferate, users increasingly demand intuitive ways to create diverse, high-quality portrait collections. In this work, we introduce Portrait Collection Generation (PCG), a novel task that generates coherent portrait collections by editing a reference portrait image throu
Composed Image Retrieval (CIR) aims to retrieve target images from candidate set using a hybrid-modality query consisting of a reference image and a relative caption that describes the user intent. Recent studies attempt to utilize Vision-Language Pre-training Models (VLPMs) with various fusion stra…
Image retrieval with composed query (IR-CQ) is a challenging task since it aims to retrieve the target image according to a hybrid-modality query which consists of a reference image and a text modifier. Previous approaches mainly focus on designing various multi-modal fusion modules to fuse the hybr…