statistiche ricercatore

Nome	#
Denoise and Contrast for Category Agnostic Shape Completion, file e384c433-dca8-d4b2-e053-9f05fe0a1d67	33
Joint supervised and self-supervised learning for 3D real world challenges, file e384c433-ce49-d4b2-e053-9f05fe0a1d67	12
Self-Supervision for 3D Real-World Challenges, file e384c433-b7be-d4b2-e053-9f05fe0a1d67	6
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers, file 5b032aee-329c-44c9-a02a-ae2d41d728e9	4
A Backpack Full of Skills: Egocentric Video Understanding with Diverse Task Perspectives, file 1c50cbc5-5823-4de8-a613-2e391b801728	3
End-to-End Learning to Grasp via Sampling From Object Point Clouds, file 584169a7-a77a-4c82-be85-543eeeb7b361	3
End-to-End Learning to Grasp via Sampling from Object Point Clouds, file 80c21f46-72ae-4d29-b26b-3c52db0ec4cd	3
Joint supervised and self-supervised learning for 3D real world challenges, file e384c433-d13f-d4b2-e053-9f05fe0a1d67	3
3DOS: Towards 3D Open Set Learning - Benchmarking and Understanding Semantic Novelty Detection on Point Clouds, file f88bcf0f-60de-4e33-acd2-924f1ef05cb1	2
Joint Supervised and Self-Supervised Learning for 3D Real World Challenges, file 44068dc5-4fe0-4de3-8b54-94f85d9a8ca3	1
End-to-End Learning to Grasp via Sampling From Object Point Clouds, file dc900ac6-b2b1-434c-8b7d-0e9fc408eaee	1
Self-Supervision for 3D Real-World Challenges, file e384c433-b383-d4b2-e053-9f05fe0a1d67	1
Totale	72

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2020/2021	6	0	0	0	0	0	0	0	0	0	0	3	3
2021/2022	35	0	2	7	4	3	2	1	2	3	6	2	3
2022/2023	20	3	0	6	1	4	4	0	0	2	0	0	0
2023/2024	11	0	0	0	1	2	0	1	0	0	7	0	0
Totale													72

PORTO @ Archivio Istituzionale della Ricerca