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cs.CV2026
Stream3D-VLM: Online 3D Spatial Understanding with Incremental Geometry Priors
Hanxun Yu, Xuan Qu, Lei Ke +4
Despite advances in 3D scene understanding, existing 3D Large Multimodal Models operate in offline settings, requiring complete scene observations or predefined video clips. In thi…
cs.CV2026
Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders
Boqiang Zhang, Lei Ke, Ruihan Yang +5
Vision Language Model (VLM) development has largely relied on scaling model size, which hinders deployment on compute-constrained mobile and edge devices such as smartphones and ro…
cs.CV2026
Boosting Segment Anything Model to Generalize Visually Non-Salient Scenarios
Guangqian Guo, Pengfei Chen, Yong Guo +3
Segment Anything Model (SAM), known for its remarkable zero-shot segmentation capabilities, has garnered significant attention in the community. Nevertheless, its performance is ch…