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20232026
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cs.CV2026

Long Time No See: Benchmarking VLMs for Out-of-Sight Spatiotemporal Reasoning in Egocentric Videos

Fangzhou Ma, Ivo Alexander Ban, Eren Homburg +5

Real-world AI systems must reason about objects that are no longer visible: an AR assistant guiding a user back to an object used earlier, a household robot retrieving an item some…

cs.CV2026

Hand-4DGS: Feed-Forward 3D Gaussian Splatting for 4D Hand Reconstruction from Egocentric Videos

Jeongmin Bae, Seoha Kim, Marc Pollefeys +3

Dynamic 3D hand reconstruction from egocentric videos is essential for next-generation computing platforms such as AR/VR and AI glasses. Despite its importance, most prior works fo…

cs.CV2026

AdaptToken: Entropy-based Adaptive Token Selection for MLLM Long Video Understanding

Haozhe Qi, Kevin Qu, Mahdi Rad +3

Long video understanding remains challenging for Multi-modal Large Language Models (MLLMs) due to high memory costs and context-length limits. Prior approaches mitigate this by sco…

cs.CV2026

CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling

Sayan Deb Sarkar, Rémi Pautrat, Ondrej Miksik +4

Video Language Models (VideoLMs) enable AI systems to understand temporal dynamics in videos. To fit within the maximum context window constraint, current methods use keyframe samp…

cs.CV2026

Loc3R-VLM: Language-based Localization and 3D Reasoning with Vision-Language Models

Kevin Qu, Haozhe Qi, Mihai Dusmanu +3

Multimodal Large Language Models (MLLMs) have made impressive progress in connecting vision and language, but they still struggle with spatial understanding and viewpoint-aware rea…