GraspIT provides ~316k annotated RGBD frames with ~2.3M slip-test-validated 6-DoF grasp candidates and a bidirectional sim-to-real registration pipeline, all released as open-source Docker containers.
Siglip 2: Multilingual vision- language encoders with improved semantic understanding, localization, and dense features
2 Pith papers cite this work. Polarity classification is still indexing.
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Supervised and contrastive pretraining yield stronger linear separability than masked reconstruction or self-distillation on a three-class emerald grading task, with reconstruction improving under nonlinear probes.
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GraspIT: A Dataset Bridging the Sim-to-Real gap and back for Validated Grasping SE(3) Pose Generation
GraspIT provides ~316k annotated RGBD frames with ~2.3M slip-test-validated 6-DoF grasp candidates and a bidirectional sim-to-real registration pipeline, all released as open-source Docker containers.
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Pretraining Objective Matters in Extreme Low-Data FGVC: A Backbone-Controlled Study
Supervised and contrastive pretraining yield stronger linear separability than masked reconstruction or self-distillation on a three-class emerald grading task, with reconstruction improving under nonlinear probes.