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pro vyhledávání: '"Zhang, Chenshuang"'
There is a growing concern about applying batch normalization (BN) in adversarial training (AT), especially when the model is trained on both adversarial samples and clean samples (termed Hybrid-AT). With the assumption that adversarial and clean sam
Externí odkaz:
http://arxiv.org/abs/2403.19150
We establish rigorous benchmarks for visual perception robustness. Synthetic images such as ImageNet-C, ImageNet-9, and Stylized ImageNet provide specific type of evaluation over synthetic corruptions, backgrounds, and textures, yet those robustness
Externí odkaz:
http://arxiv.org/abs/2403.18775
Segment anything model (SAM), as the name suggests, is claimed to be capable of cutting out any object and demonstrates impressive zero-shot transfer performance with the guidance of prompts. However, there is currently a lack of comprehensive evalua
Externí odkaz:
http://arxiv.org/abs/2306.07713
Autor:
Zhang, Chaoning, Qiao, Yu, Tariq, Shehbaz, Zheng, Sheng, Zhang, Chenshuang, Li, Chenghao, Shin, Hyundong, Hong, Choong Seon
In contrast to the human vision that mainly depends on the shape for recognizing the objects, deep image recognition models are widely known to be biased toward texture. Recently, Meta research team has released the first foundation model for image s
Externí odkaz:
http://arxiv.org/abs/2311.11465
Autor:
Zhang, Chaoning, Puspitasari, Fachrina Dewi, Zheng, Sheng, Li, Chenghao, Qiao, Yu, Kang, Taegoo, Shan, Xinru, Zhang, Chenshuang, Qin, Caiyan, Rameau, Francois, Lee, Lik-Hang, Bae, Sung-Ho, Hong, Choong Seon
Segment anything model (SAM) developed by Meta AI Research has recently attracted significant attention. Trained on a large segmentation dataset of over 1 billion masks, SAM is capable of segmenting any object on a certain image. In the original SAM
Externí odkaz:
http://arxiv.org/abs/2306.06211
Segment Anything Model (SAM) has attracted significant attention recently, due to its impressive performance on various downstream tasks in a zero-short manner. Computer vision (CV) area might follow the natural language processing (NLP) area to emba
Externí odkaz:
http://arxiv.org/abs/2305.00866
Autor:
Zhang, Chaoning, Zhang, Chenshuang, Li, Chenghao, Qiao, Yu, Zheng, Sheng, Dam, Sumit Kumar, Zhang, Mengchun, Kim, Jung Uk, Kim, Seong Tae, Choi, Jinwoo, Park, Gyeong-Moon, Bae, Sung-Ho, Lee, Lik-Hang, Hui, Pan, Kweon, In So, Hong, Choong Seon
OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quick
Externí odkaz:
http://arxiv.org/abs/2304.06488
Autor:
Zhang, Mengchun, Qamar, Maryam, Kang, Taegoo, Jung, Yuna, Zhang, Chenshuang, Bae, Sung-Ho, Zhang, Chaoning
Diffusion models have become a new SOTA generative modeling method in various fields, for which there are multiple survey works that provide an overall survey. With the number of articles on diffusion models increasing exponentially in the past few y
Externí odkaz:
http://arxiv.org/abs/2304.01565
Autor:
Zhang, Chenshuang, Zhang, Chaoning, Zheng, Sheng, Zhang, Mengchun, Qamar, Maryam, Bae, Sung-Ho, Kweon, In So
Generative AI has demonstrated impressive performance in various fields, among which speech synthesis is an interesting direction. With the diffusion model as the most popular generative model, numerous works have attempted two active tasks: text to
Externí odkaz:
http://arxiv.org/abs/2303.13336
Autor:
Zhang, Chaoning, Zhang, Chenshuang, Zheng, Sheng, Qiao, Yu, Li, Chenghao, Zhang, Mengchun, Dam, Sumit Kumar, Thwal, Chu Myaet, Tun, Ye Lin, Huy, Le Luang, kim, Donguk, Bae, Sung-Ho, Lee, Lik-Hang, Yang, Yang, Shen, Heng Tao, Kweon, In So, Hong, Choong Seon
As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With such overwhelming media coverage, it is almost impossible for us to miss
Externí odkaz:
http://arxiv.org/abs/2303.11717