2 papers
cs.RO2026
GSAM: A Generalizable and Safe Robotic Framework for Articulated Object Manipulation
Beichen Shao, Mengying Xie, Heng Su +5
Articulated object manipulation is a unique challenge for service robots. Existing methods employ end-to-end policy learning, visionmotion planning, and large-language/visual-langu…
cs.CV2026
What can Computer Vision learn from Ranganathan?
Mayukh Bagchi, Fausto Giunchiglia
The Semantic Gap Problem (SGP) in Computer Vision (CV) arises from the misalignment between visual and lexical semantics leading to flawed CV dataset design and CV benchmarks. This…