Zobrazeno 1 - 10
of 6 661
pro vyhledávání: '"A. Shiran"'
Autor:
Zhang, David Junhao, Paiss, Roni, Zada, Shiran, Karnad, Nikhil, Jacobs, David E., Pritch, Yael, Mosseri, Inbar, Shou, Mike Zheng, Wadhwa, Neal, Ruiz, Nataniel
Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided videos that are not generated by a video model. In this paper, we pres
Externí odkaz:
http://arxiv.org/abs/2411.05003
Autor:
Ma, Jingwei, Lu, Erika, Paiss, Roni, Zada, Shiran, Holynski, Aleksander, Dekel, Tali, Curless, Brian, Rubinstein, Michael, Cole, Forrester
Panoramic image stitching provides a unified, wide-angle view of a scene that extends beyond the camera's field of view. Stitching frames of a panning video into a panoramic photograph is a well-understood problem for stationary scenes, but when obje
Externí odkaz:
http://arxiv.org/abs/2410.13832
Autor:
Yuan, Shiran, Zhao, Hao
We address an important problem in ecology called Species Distribution Modeling (SDM), whose goal is to predict whether a species exists at a certain position on Earth. In particular, we tackle a challenging version of this task, where we learn from
Externí odkaz:
http://arxiv.org/abs/2410.10937
We present a practical distillation approach to fine-tune LLMs for invoking tools in real-time applications. We focus on visual editing tasks; specifically, we modify images and videos by interpreting user stylistic requests, specified in natural lan
Externí odkaz:
http://arxiv.org/abs/2410.02952
With the popularity of cellular phones, events are often recorded by multiple devices from different locations and shared on social media. Several different recordings could be found for many events. Such recordings are usually noisy, where noise for
Externí odkaz:
http://arxiv.org/abs/2408.17434
Autor:
Yang, Xuemei, Zhang, Dunxiang, Wang, Weizhe, Tian, Kan, He, Linzhen, Guo, Jinmiao, Hu, Bo, Pu, Tao, Li, Wenlong, Sun, Shiran, Ding, Chunmei, Wu, Han, Li, Kenkai, Peng, Yujie, Li, Jianshu, Leng, Yuxin, Liang, Houkun
High-power broadband tunable long-wavelength infrared (LWIR) femtosecond lasers operating at fingerprint wavelengths of 7-14 {\mu}m hold significant promise across a range of applications, including molecular hyperspectral imaging, strong-field light
Externí odkaz:
http://arxiv.org/abs/2408.13789
Large Language Models (LLMs) have gained widespread global adoption, showcasing advanced linguistic capabilities across multiple of languages. There is a growing interest in academia to use these models to simulate and study human behaviors. However,
Externí odkaz:
http://arxiv.org/abs/2408.02143
Autor:
Chefer, Hila, Zada, Shiran, Paiss, Roni, Ephrat, Ariel, Tov, Omer, Rubinstein, Michael, Wolf, Lior, Dekel, Tali, Michaeli, Tomer, Mosseri, Inbar
Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its infancy, primar
Externí odkaz:
http://arxiv.org/abs/2407.08674
Accurate and efficient prediction of aeroengine performance is of paramount importance for engine design, maintenance, and optimization endeavours. However, existing methodologies often struggle to strike an optimal balance among predictive accuracy,
Externí odkaz:
http://arxiv.org/abs/2407.00501
Large Language Models (LLMs), such as ChatGPT, are widely used to generate content for various purposes and audiences. However, these models may not reflect the cultural and emotional diversity of their users, especially for low-resource languages. I
Externí odkaz:
http://arxiv.org/abs/2406.19504