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pro vyhledávání: '"Sharma, Sarthak"'
In this work, we present, AVR application for audio-visual humor detection. While humor detection has traditionally centered around textual analysis, recent advancements have spotlighted multimodal approaches. However, these methods lean on textual c
Externí odkaz:
http://arxiv.org/abs/2406.10448
Autor:
Dewangan, Vikrant, Sharma, Basant, Choudhary, Tushar, Sharma, Sarthak, Aanegola, Aakash, Singh, Arun K., Krishna, K. Madhava
Autonomous driving requires accurate reasoning of the location of objects from raw sensor data. Recent end-to-end learning methods go from raw sensor data to a trajectory output via Bird's Eye View(BEV) segmentation as an interpretable intermediate r
Externí odkaz:
http://arxiv.org/abs/2306.04939
Autor:
Harithas, Sudarshan S, Singh, Gurkirat, Chavan, Aneesh, Sharma, Sarthak, Patni, Suraj, Arora, Chetan, Krishna, K. Madhava
We focus on the problem of LiDAR point cloud based loop detection (or Finding) and closure (LDC) in a multi-agent setting. State-of-the-art (SOTA) techniques directly generate learned embeddings of a given point cloud, require large data transfers, a
Externí odkaz:
http://arxiv.org/abs/2304.01074
Autor:
Sharma, Sarthak, Nair, Unnikrishnan R., Parihar, Udit Singh, S, Midhun Menon, Vidapanakal, Srikanth
Autonomous driving requires efficient reasoning about the location and appearance of the different agents in the scene, which aids in downstream tasks such as object detection, object tracking, and path planning. The past few years have witnessed a s
Externí odkaz:
http://arxiv.org/abs/2211.04557
Autor:
Nair, Unnikrishnan R, Sharma, Sarthak, Parihar, Udit Singh, Menon, Midhun S, Vidapanakal, Srikanth
We present the first prize solution to NeurIPS 2021 - AWS Deepracer Challenge. In this competition, the task was to train a reinforcement learning agent (i.e. an autonomous car), that learns to drive by interacting with its environment, a simulated t
Externí odkaz:
http://arxiv.org/abs/2205.07481
Autonomous driving requires efficient reasoning about the Spatio-temporal nature of the semantics of the scene. Recent approaches have successfully amalgamated the traditional modular architecture of an autonomous driving stack comprising perception,
Externí odkaz:
http://arxiv.org/abs/2205.05551
Autor:
Venkatesh, Rahul, Karmali, Tejan, Sharma, Sarthak, Ghosh, Aurobrata, Babu, R. Venkatesh, Jeni, László A., Singh, Maneesh
Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit representations using meshes and point clouds. However, most such approach
Externí odkaz:
http://arxiv.org/abs/2106.05779
Publikováno v:
In Heliyon 15 January 2024 10(1)
High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classical discrete shape representations using point clouds, voxels and meshe
Externí odkaz:
http://arxiv.org/abs/2011.02570
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