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pro vyhledávání: '"A. Krishna Kumar"'
Autor:
Dubey, Sushim
Publikováno v:
Indian Historical Review; Dec2023, Vol. 50 Issue 2, p345-348, 4p
Akademický článek
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Autor:
Tilak, Jandhyala B. G.
Publikováno v:
Social Change; September 2024, Vol. 54 Issue: 3 p440-443, 4p
Autor:
Ding, Zihan, Jin, Chi, Liu, Difan, Zheng, Haitian, Singh, Krishna Kumar, Zhang, Qiang, Kang, Yan, Lin, Zhe, Liu, Yuchen
Diffusion probabilistic models have shown significant progress in video generation; however, their computational efficiency is limited by the large number of sampling steps required. Reducing sampling steps often compromises video quality or generati
Externí odkaz:
http://arxiv.org/abs/2412.15689
Autor:
Cha, Junuk, Ren, Mengwei, Singh, Krishna Kumar, Zhang, He, Hold-Geoffroy, Yannick, Yoon, Seunghyun, Jung, HyunJoon, Yoon, Jae Shin, Baek, Seungryul
We present a lighting-aware image editing pipeline that, given a portrait image and a text prompt, performs single image relighting. Our model modifies the lighting and color of both the foreground and background to align with the provided text descr
Externí odkaz:
http://arxiv.org/abs/2412.13734
Autor:
Tanveer, Maham, Zhou, Yang, Niklaus, Simon, Amiri, Ali Mahdavi, Zhang, Hao, Singh, Krishna Kumar, Zhao, Nanxuan
By generating plausible and smooth transitions between two image frames, video inbetweening is an essential tool for video editing and long video synthesis. Traditional works lack the capability to generate complex large motions. While recent video g
Externí odkaz:
http://arxiv.org/abs/2412.13190
Maxwell's equations are the fundamental equations for understanding electric and magnetic field interactions and play a crucial role in designing and optimizing sensor systems like capacitive touch sensors, which are widely prevalent in automotive sw
Externí odkaz:
http://arxiv.org/abs/2412.08650
Autor:
Yoon, Jae Shin, Shu, Zhixin, Ren, Mengwei, Zhang, Xuaner, Hold-Geoffroy, Yannick, Singh, Krishna Kumar, Zhang, He
We introduce a high-fidelity portrait shadow removal model that can effectively enhance the image of a portrait by predicting its appearance under disturbing shadows and highlights. Portrait shadow removal is a highly ill-posed problem where multiple
Externí odkaz:
http://arxiv.org/abs/2410.05525
Autor:
Li, Yuheng, Liu, Haotian, Cai, Mu, Li, Yijun, Shechtman, Eli, Lin, Zhe, Lee, Yong Jae, Singh, Krishna Kumar
In this paper, we introduce a model designed to improve the prediction of image-text alignment, targeting the challenge of compositional understanding in current visual-language models. Our approach focuses on generating high-quality training dataset
Externí odkaz:
http://arxiv.org/abs/2410.00905
Publikováno v:
Current Science, 2015 Jun . 108(12), 2277-2278.
Externí odkaz:
http://www.jstor.org/stable/24905669