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pro vyhledávání: '"Ganz, Roy"'
Adversarial training aims to defend against *adversaries*: malicious opponents whose sole aim is to harm predictive performance in any way possible - a rather harsh perspective, which we assert results in unnecessarily conservative models. Instead, w
Externí odkaz:
http://arxiv.org/abs/2406.11458
The recently introduced Consistency models pose an efficient alternative to diffusion algorithms, enabling rapid and good quality image synthesis. These methods overcome the slowness of diffusion models by directly mapping noise to data, while mainta
Externí odkaz:
http://arxiv.org/abs/2405.16260
Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provided input masks remains a challe
Externí odkaz:
http://arxiv.org/abs/2404.18212
Autor:
Ganz, Roy, Kittenplon, Yair, Aberdam, Aviad, Avraham, Elad Ben, Nuriel, Oren, Mazor, Shai, Litman, Ron
Vision-Language (VL) models have gained significant research focus, enabling remarkable advances in multimodal reasoning. These architectures typically comprise a vision encoder, a Large Language Model (LLM), and a projection module that aligns visua
Externí odkaz:
http://arxiv.org/abs/2402.05472
Autor:
Blau, Tsachi, Fogel, Sharon, Ronen, Roi, Golts, Alona, Ganz, Roy, Avraham, Elad Ben, Aberdam, Aviad, Tsiper, Shahar, Litman, Ron
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA), leading methods focus on the single-page setting, while documents can span hundre
Externí odkaz:
http://arxiv.org/abs/2401.03411
Autor:
Ganz, Roy, Elad, Michael
Perceptually Aligned Gradients (PAG) refer to an intriguing property observed in robust image classification models, wherein their input gradients align with human perception and pose semantic meanings. While this phenomenon has gained significant re
Externí odkaz:
http://arxiv.org/abs/2306.16805
The advent of vision-language pre-training techniques enhanced substantial progress in the development of models for image captioning. However, these models frequently produce generic captions and may omit semantically important image details. This l
Externí odkaz:
http://arxiv.org/abs/2305.17718
It has been recently discovered that adversarially trained classifiers exhibit an intriguing property, referred to as perceptually aligned gradients (PAG). PAG implies that the gradients of such classifiers possess a meaningful structure, aligned wit
Externí odkaz:
http://arxiv.org/abs/2303.15409
Autor:
Aberdam, Aviad, Bensaïd, David, Golts, Alona, Ganz, Roy, Nuriel, Oren, Tichauer, Royee, Mazor, Shai, Litman, Ron
Reading text in real-world scenarios often requires understanding the context surrounding it, especially when dealing with poor-quality text. However, current scene text recognizers are unaware of the bigger picture as they operate on cropped text im
Externí odkaz:
http://arxiv.org/abs/2301.07464
Visual Question Answering (VQA) and Image Captioning (CAP), which are among the most popular vision-language tasks, have analogous scene-text versions that require reasoning from the text in the image. Despite their obvious resemblance, the two are t
Externí odkaz:
http://arxiv.org/abs/2301.07389