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cs.CV2026
Learning to Perceive "Where": Spatial Pretext Tasks for Robust Self-Supervised Learning
Yang Shen, Yusen Cai, Weronika Hryniewska-Guzik +2
Existing self-supervised learning (SSL) methods primarily learn object-invariant representations but often neglect the spatial structure and relationships among object parts. To ad…
cs.CV2026
MOSIV: Multi-Object System Identification from Videos
Chunjiang Liu, Xiaoyuan Wang, Qingran Lin +9
We introduce the challenging problem of multi-object system identification from videos, for which prior methods are ill-suited due to their focus on single-object scenes or discret…
cs.CV2026
FMMC: Harnessing the Power of Foundation Models for Accurate Material Classification
Qingran Lin, Fengwei Yang, Chaolun Zhu
Material classification has emerged as a critical task in computer vision and graphics, supporting the assignment of accurate material properties to a wide range of digital and rea…