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of 3
pro vyhledávání: '"Patni, Suraj"'
Autor:
Spencer, Jaime, Tosi, Fabio, Poggi, Matteo, Arora, Ripudaman Singh, Russell, Chris, Hadfield, Simon, Bowden, Richard, Zhou, GuangYuan, Li, ZhengXin, Rao, Qiang, Bao, YiPing, Liu, Xiao, Kim, Dohyeong, Kim, Jinseong, Kim, Myunghyun, Lavreniuk, Mykola, Li, Rui, Mao, Qing, Wu, Jiang, Zhu, Yu, Sun, Jinqiu, Zhang, Yanning, Patni, Suraj, Agarwal, Aradhye, Arora, Chetan, Sun, Pihai, Jiang, Kui, Wu, Gang, Liu, Jian, Liu, Xianming, Jiang, Junjun, Zhang, Xidan, Wei, Jianing, Wang, Fangjun, Tan, Zhiming, Wang, Jiabao, Luginov, Albert, Shahzad, Muhammad, Hosseini, Seyed, Trajcevski, Aleksander, Elder, James H.
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-Patches dataset, featuring complex scenes in natural and indoor settin
Externí odkaz:
http://arxiv.org/abs/2404.16831
In the absence of parallax cues, a learning-based single image depth estimation (SIDE) model relies heavily on shading and contextual cues in the image. While this simplicity is attractive, it is necessary to train such models on large and varied dat
Externí odkaz:
http://arxiv.org/abs/2403.18807
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