Graph-based medical image segmentation represents anatomical structures using boundary graphs, providing fixed-topology landmarks and inherent population-level ...

Deep learning has significantly advanced automated brain tumor diagnosis, yet clinical adoption remains limited by interpretability and computational constraint...

Text-to-image retrieval is a fundamental task in vision-language learning, yet in real-world scenarios it is often challenged by short and underspecified user q...

Vision-Language-Action (VLA) models are advancing autonomous driving by replacing modular pipelines with unified end-to-end architectures. However, current VLAs...

Medical image processing demands specialized software that handles high-dimensional volumetric data, heterogeneous file formats, and domain-specific training pr...

!소상공인 매장 업무 효율화 AI 솔루션 ‘모코플렉스’, AI 헤어 스타일링 ‘스타일싱크’ 출시https://besuccess.com/wp-content/uploads/2026/02/%EC%9D%B4%EB%AF%B8%EC%A7%80-%EB%AA%A8%EC%BD%94%ED%94%8C%EB...

Unified multimodal models can both understand and generate visual content within a single architecture. Existing models, however, remain data-hungry and too hea...

We propose tttLRM, a novel large 3D reconstruction model that leverages a Test-Time Training (TTT) layer to enable long-context, autoregressive 3D reconstructio...

Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence i...

Current feed-forward 3D/4D reconstruction systems rely on dense geometry and pose supervision -- expensive to obtain at scale and particularly scarce for dynami...

Estimating simulation-ready scenes from real-world observations is crucial for downstream planning and policy learning tasks. Regretfully, existing methods stru...

Data visualization rules-derived from decades of research in design and perception-ensure trustworthy chart communication. While prior work has shown that large...