Zobrazeno 1 - 10
of 1 763
pro vyhledávání: '"Davis, Larry"'
Autor:
Wu, Zuxuan, Weng, Zejia, Peng, Wujian, Yang, Xitong, Li, Ang, Davis, Larry S., Jiang, Yu-Gang
Despite significant results achieved by Contrastive Language-Image Pretraining (CLIP) in zero-shot image recognition, limited effort has been made exploring its potential for zero-shot video recognition. This paper presents Open-VCLIP++, a simple yet
Externí odkaz:
http://arxiv.org/abs/2310.05010
We present FlexNeRF, a method for photorealistic freeviewpoint rendering of humans in motion from monocular videos. Our approach works well with sparse views, which is a challenging scenario when the subject is exhibiting fast/complex motions. We pro
Externí odkaz:
http://arxiv.org/abs/2303.14368
Autor:
Wang, Junke, Li, Zhenxin, Zhang, Chao, Chen, Jingjing, Wu, Zuxuan, Davis, Larry S., Jiang, Yu-Gang
Online media data, in the forms of images and videos, are becoming mainstream communication channels. However, recent advances in deep learning, particularly deep generative models, open the doors for producing perceptually convincing images and vide
Externí odkaz:
http://arxiv.org/abs/2212.05667
Autor:
Wang, Jun, Gao, Mingfei, Hu, Yuqian, Selvaraju, Ramprasaath R., Ramaiah, Chetan, Xu, Ran, JaJa, Joseph F., Davis, Larry S.
Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers from insufficient human-labeled question-answer (QA) pairs. However, we o
Externí odkaz:
http://arxiv.org/abs/2208.01813
We present Neural Space-filling Curves (SFCs), a data-driven approach to infer a context-based scan order for a set of images. Linear ordering of pixels forms the basis for many applications such as video scrambling, compression, and auto-regressive
Externí odkaz:
http://arxiv.org/abs/2204.08453
Autor:
Ehrlich, Max, Barker, Jon, Padmanabhan, Namitha, Davis, Larry, Tao, Andrew, Catanzaro, Bryan, Shrivastava, Abhinav
Video compression is a central feature of the modern internet powering technologies from social media to video conferencing. While video compression continues to mature, for many compression settings, quality loss is still noticeable. These settings
Externí odkaz:
http://arxiv.org/abs/2202.00011
Generation of photo-realistic images, semantic editing and representation learning are a few of many potential applications of high resolution generative models. Recent progress in GANs have established them as an excellent choice for such tasks. How
Externí odkaz:
http://arxiv.org/abs/2112.04598