Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sarkar, Sayan Deb"'
Autor:
Parida, Shantipriya, Abdulmumin, Idris, Muhammad, Shamsuddeen Hassan, Bose, Aneesh, Kohli, Guneet Singh, Ahmad, Ibrahim Said, Kotwal, Ketan, Sarkar, Sayan Deb, Bojar, Ondřej, Kakudi, Habeebah Adamu
This paper presents HaVQA, the first multimodal dataset for visual question-answering (VQA) tasks in the Hausa language. The dataset was created by manually translating 6,022 English question-answer pairs, which are associated with 1,555 unique image
Externí odkaz:
http://arxiv.org/abs/2305.17690
Building 3D scene graphs has recently emerged as a topic in scene representation for several embodied AI applications to represent the world in a structured and rich manner. With their increased use in solving downstream tasks (eg, navigation and roo
Externí odkaz:
http://arxiv.org/abs/2304.14880
HO-3D is a dataset providing image sequences of various hand-object interaction scenarios annotated with the 3D pose of the hand and the object and was originally introduced as HO-3D_v2. The annotations were obtained automatically using an optimizati
Externí odkaz:
http://arxiv.org/abs/2107.00887
We propose a robust and accurate method for estimating the 3D poses of two hands in close interaction from a single color image. This is a very challenging problem, as large occlusions and many confusions between the joints may happen. State-of-the-a
Externí odkaz:
http://arxiv.org/abs/2104.14639
Autor:
Hampali, Shreyas, Stekovic, Sinisa, Sarkar, Sayan Deb, Kumar, Chetan Srinivasa, Fraundorfer, Friedrich, Lepetit, Vincent
We explore how a general AI algorithm can be used for 3D scene understanding to reduce the need for training data. More exactly, we propose a modification of the Monte Carlo Tree Search (MCTS) algorithm to retrieve objects and room layouts from noisy
Externí odkaz:
http://arxiv.org/abs/2103.07969
Autor:
Stekovic, Sinisa, Hampali, Shreyas, Rad, Mahdi, Sarkar, Sayan Deb, Fraundorfer, Friedrich, Lepetit, Vincent
We present a novel method to reconstruct the 3D layout of a room (walls, floors, ceilings) from a single perspective view in challenging conditions, by contrast with previous single-view methods restricted to cuboid-shaped layouts. This input view ca
Externí odkaz:
http://arxiv.org/abs/2001.02149
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
We propose a robust and accurate method for estimating the 3D poses of two hands in close interaction from a single color image. This is a very challenging problem, as large occlusions and many confusions between the joints may happen. State-of-the-a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d352ee0ac5f5f5ccc76e0a7b89d45836
https://doi.org/10.1109/cvpr52688.2022.01081
https://doi.org/10.1109/cvpr52688.2022.01081
Publikováno v:
AIP Conference Proceedings; 2023, Vol. 2977 Issue 1, p1-12, 12p
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference