Zobrazeno 1 - 10
of 11 186
pro vyhledávání: '"A. Krishna Kumar"'
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
Autor:
Jiang, Yuming, Zhao, Nanxuan, Liu, Qing, Singh, Krishna Kumar, Yang, Shuai, Loy, Chen Change, Liu, Ziwei
Group portrait editing is highly desirable since users constantly want to add a person, delete a person, or manipulate existing persons. It is also challenging due to the intricate dynamics of human interactions and the diverse gestures. In this work
Externí odkaz:
http://arxiv.org/abs/2409.14379
Theoretical studies on the representation power of GNNs have been centered around understanding the equivalence of GNNs, using WL-Tests for detecting graph isomorphism. In this paper, we argue that such equivalence ignores the accompanying optimizati
Externí odkaz:
http://arxiv.org/abs/2408.09266
Autor:
Jayagopal, Aishwarya, Xue, Hansheng, He, Ziyang, Walsh, Robert J., Hariprasannan, Krishna Kumar, Tan, David Shao Peng, Tan, Tuan Zea, Pitt, Jason J., Jeyasekharan, Anand D., Rajan, Vaibhav
Cancer remains a global challenge due to its growing clinical and economic burden. Its uniquely personal manifestation, which makes treatment difficult, has fuelled the quest for personalized treatment strategies. Thus, genomic profiling is increasin
Externí odkaz:
http://arxiv.org/abs/2402.10551
Autor:
Pan, Boxiao, Xu, Zhan, Huang, Chun-Hao Paul, Singh, Krishna Kumar, Zhou, Yang, Guibas, Leonidas J., Yang, Jimei
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing background that aligns with the motion and appearance of the foreground
Externí odkaz:
http://arxiv.org/abs/2401.10822