Zobrazeno 1 - 10
of 391
pro vyhledávání: '"Sinha Animesh A"'
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
Autor:
Suri, Saksham, Xiao, Fanyi, Sinha, Animesh, Culatana, Sean Chang, Krishnamoorthi, Raghuraman, Zhu, Chenchen, Shrivastava, Abhinav
Recently diffusion models have shown improvement in synthetic image quality as well as better control in generation. We motivate and present Gen2Det, a simple modular pipeline to create synthetic training data for object detection for free by leverag
Externí odkaz:
http://arxiv.org/abs/2312.04566
Autor:
Chen, Shoufa, Xu, Mengmeng, Ren, Jiawei, Cong, Yuren, He, Sen, Xie, Yanping, Sinha, Animesh, Luo, Ping, Xiang, Tao, Perez-Rua, Juan-Manuel
In this study, we explore Transformer-based diffusion models for image and video generation. Despite the dominance of Transformer architectures in various fields due to their flexibility and scalability, the visual generative domain primarily utilize
Externí odkaz:
http://arxiv.org/abs/2312.04557
Autor:
Najdenkoska, Ivona, Sinha, Animesh, Dubey, Abhimanyu, Mahajan, Dhruv, Ramanathan, Vignesh, Radenovic, Filip
We propose Context Diffusion, a diffusion-based framework that enables image generation models to learn from visual examples presented in context. Recent work tackles such in-context learning for image generation, where a query image is provided alon
Externí odkaz:
http://arxiv.org/abs/2312.03584
Autor:
Sinha, Animesh, Sun, Bo, Kalia, Anmol, Casanova, Arantxa, Blanchard, Elliot, Yan, David, Zhang, Winnie, Nelli, Tony, Chen, Jiahui, Shah, Hardik, Yu, Licheng, Singh, Mitesh Kumar, Ramchandani, Ankit, Sanjabi, Maziar, Gupta, Sonal, Bearman, Amy, Mahajan, Dhruv
We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models (LDMs) in a distinct domain with high visual quality, prompt alignment and scene diversity. We choose sticker image generation as the target domain, as the images significantl
Externí odkaz:
http://arxiv.org/abs/2311.10794
Autor:
Mirchandani, Suvir, Yu, Licheng, Wang, Mengjiao, Sinha, Animesh, Jiang, Wenwen, Xiang, Tao, Zhang, Ning
Multimodal tasks in the fashion domain have significant potential for e-commerce, but involve challenging vision-and-language learning problems - e.g., retrieving a fashion item given a reference image plus text feedback from a user. Prior works on m
Externí odkaz:
http://arxiv.org/abs/2210.15028
Autor:
Azad, Utkarsh, Sinha, Animesh
Publikováno v:
Quantum Inf Process 22, 256 (2023)
We present qLEET, an open-source Python package for studying parameterized quantum circuits (PQCs), which are widely used in various variational quantum algorithms (VQAs) and quantum machine learning (QML) algorithms. qLEET enables the computation of
Externí odkaz:
http://arxiv.org/abs/2205.02095
Autor:
Yu, Licheng, Chen, Jun, Sinha, Animesh, Wang, Mengjiao MJ, Chen, Hugo, Berg, Tamara L., Zhang, Ning
We introduce CommerceMM - a multimodal model capable of providing a diverse and granular understanding of commerce topics associated to the given piece of content (image, text, image+text), and having the capability to generalize to a wide range of t
Externí odkaz:
http://arxiv.org/abs/2202.07247
Publikováno v:
BMC Bioinformatics, Vol 7, Iss Suppl 5, p S7 (2006)
Abstract Background Pemphigus vulgaris (PV) is a severe autoimmune blistering skin disorder that is strongly associated with major histocompatibility complex class II alleles DRB1*0402 and DQB1*0503. The target antigen of PV, desmoglein 3 (Dsg3), is
Externí odkaz:
https://doaj.org/article/f1395e649bdb407cb2b6db7c392adbb6
