Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Zhang, Peizhao"'
Autor:
Polyak, Adam, Zohar, Amit, Brown, Andrew, Tjandra, Andros, Sinha, Animesh, Lee, Ann, Vyas, Apoorv, Shi, Bowen, Ma, Chih-Yao, Chuang, Ching-Yao, Yan, David, Choudhary, Dhruv, Wang, Dingkang, Sethi, Geet, Pang, Guan, Ma, Haoyu, Misra, Ishan, Hou, Ji, Wang, Jialiang, Jagadeesh, Kiran, Li, Kunpeng, Zhang, Luxin, Singh, Mannat, Williamson, Mary, Le, Matt, Yu, Matthew, Singh, Mitesh Kumar, Zhang, Peizhao, Vajda, Peter, Duval, Quentin, Girdhar, Rohit, Sumbaly, Roshan, Rambhatla, Sai Saketh, Tsai, Sam, Azadi, Samaneh, Datta, Samyak, Chen, Sanyuan, Bell, Sean, Ramaswamy, Sharadh, Sheynin, Shelly, Bhattacharya, Siddharth, Motwani, Simran, Xu, Tao, Li, Tianhe, Hou, Tingbo, Hsu, Wei-Ning, Yin, Xi, Dai, Xiaoliang, Taigman, Yaniv, Luo, Yaqiao, Liu, Yen-Cheng, Wu, Yi-Chiao, Zhao, Yue, Kirstain, Yuval, He, Zecheng, He, Zijian, Pumarola, Albert, Thabet, Ali, Sanakoyeu, Artsiom, Mallya, Arun, Guo, Baishan, Araya, Boris, Kerr, Breena, Wood, Carleigh, Liu, Ce, Peng, Cen, Vengertsev, Dimitry, Schonfeld, Edgar, Blanchard, Elliot, Juefei-Xu, Felix, Nord, Fraylie, Liang, Jeff, Hoffman, John, Kohler, Jonas, Fire, Kaolin, Sivakumar, Karthik, Chen, Lawrence, Yu, Licheng, Gao, Luya, Georgopoulos, Markos, Moritz, Rashel, Sampson, Sara K., Li, Shikai, Parmeggiani, Simone, Fine, Steve, Fowler, Tara, Petrovic, Vladan, Du, Yuming
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of
Externí odkaz:
http://arxiv.org/abs/2410.13720
Autor:
He, Zecheng, Sun, Bo, Juefei-Xu, Felix, Ma, Haoyu, Ramchandani, Ankit, Cheung, Vincent, Shah, Siddharth, Kalia, Anmol, Subramanyam, Harihar, Zareian, Alireza, Chen, Li, Jain, Ankit, Zhang, Ning, Zhang, Peizhao, Sumbaly, Roshan, Vajda, Peter, Sinha, Animesh
Diffusion models have demonstrated remarkable efficacy across various image-to-image tasks. In this research, we introduce Imagine yourself, a state-of-the-art model designed for personalized image generation. Unlike conventional tuning-based persona
Externí odkaz:
http://arxiv.org/abs/2409.13346
Diffusion Models (DMs) utilize an iterative denoising process to transform random noise into synthetic data. Initally proposed with a UNet structure, DMs excel at producing images that are virtually indistinguishable with or without conditioned text
Externí odkaz:
http://arxiv.org/abs/2406.11100
Autor:
Liang, Feng, Wu, Bichen, Wang, Jialiang, Yu, Licheng, Li, Kunpeng, Zhao, Yinan, Misra, Ishan, Huang, Jia-Bin, Zhang, Peizhao, Vajda, Peter, Marculescu, Diana
Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampered by the challenge of maintaining temporal consistency across video fr
Externí odkaz:
http://arxiv.org/abs/2312.17681
Latent Diffusion Models (LDMs) capture the dynamic evolution of latent variables over time, blending patterns and multimodality in a generative system. Despite the proficiency of LDM in various applications, such as text-to-image generation, facilita
Externí odkaz:
http://arxiv.org/abs/2312.05431
Autor:
Schult, Jonas, Tsai, Sam, Höllein, Lukas, Wu, Bichen, Wang, Jialiang, Ma, Chih-Yao, Li, Kunpeng, Wang, Xiaofang, Wimbauer, Felix, He, Zijian, Zhang, Peizhao, Leibe, Bastian, Vajda, Peter, Hou, Ji
Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by generating room meshes conditioned on textual style descriptions. Yet, many
Externí odkaz:
http://arxiv.org/abs/2312.05208
Autor:
Wimbauer, Felix, Wu, Bichen, Schoenfeld, Edgar, Dai, Xiaoliang, Hou, Ji, He, Zijian, Sanakoyeu, Artsiom, Zhang, Peizhao, Tsai, Sam, Kohler, Jonas, Rupprecht, Christian, Cremers, Daniel, Vajda, Peter, Wang, Jialiang
Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the major drawbacks of diffusion models is that the image generation process is costly. A large image-t
Externí odkaz:
http://arxiv.org/abs/2312.03209
Autor:
Dai, Xiaoliang, Hou, Ji, Ma, Chih-Yao, Tsai, Sam, Wang, Jialiang, Wang, Rui, Zhang, Peizhao, Vandenhende, Simon, Wang, Xiaofang, Dubey, Abhimanyu, Yu, Matthew, Kadian, Abhishek, Radenovic, Filip, Mahajan, Dhruv, Li, Kunpeng, Zhao, Yue, Petrovic, Vladan, Singh, Mitesh Kumar, Motwani, Simran, Wen, Yi, Song, Yiwen, Sumbaly, Roshan, Ramanathan, Vignesh, He, Zijian, Vajda, Peter, Parikh, Devi
Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face challenges when it comes to generating highly aesthetic images. This creat
Externí odkaz:
http://arxiv.org/abs/2309.15807
Autor:
Fu, Yonggan, Li, Yuecheng, Li, Chenghui, Saragih, Jason, Zhang, Peizhao, Dai, Xiaoliang, Lin, Yingyan
Real-time and robust photorealistic avatars for telepresence in AR/VR have been highly desired for enabling immersive photorealistic telepresence. However, there still exists one key bottleneck: the considerable computational expense needed to accura
Externí odkaz:
http://arxiv.org/abs/2304.11835
Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and Florence, are trained on large-scale datasets of image-caption pairs and achieve superior transferability and robustness on downstream tasks, but they are difficult to use in man
Externí odkaz:
http://arxiv.org/abs/2303.18232