367 citations · 900 across the 19 of their papers we have counts for
21 papers
KeyRec: Bounded Visual Memory for Streaming and Long-Video Understanding
Zihan Chen, Xuejian Rong, Xiaojuan Wang +4
Vision-language models are increasingly used to understand long videos and continuous streams. However, dense visual tokens accumulate with video duration, making long-context infe…
LiveSVG: Zero-Shot SVG Animation via Video Generation
Matan Levy, Ran Margolin, Bar Cavia +6
We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation methods struggle with comple…
Alterbute: Editing Intrinsic Attributes of Objects in Images
Tal Reiss, Daniel Winter, Matan Cohen +4
We introduce Alterbute, a diffusion-based method for editing an object's intrinsic attributes in an image. We allow changing color, texture, material, and even the shape of an obje…
LightLab: Controlling Light Sources in Images with Diffusion Models
Nadav Magar, Amir Hertz, Eric Tabellion +4
We present a simple, yet effective diffusion-based method for fine-grained, parametric control over light sources in an image. Existing relighting methods either rely on multiple i…
ObjectMate: A Recurrence Prior for Object Insertion and Subject-Driven Generation
Daniel Winter, Asaf Shul, Matan Cohen +4
This paper introduces a tuning-free method for both object insertion and subject-driven generation. The task involves composing an object, given multiple views, into a scene specif…
ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning
David Junhao Zhang, Roni Paiss, Shiran Zada +7
Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided…
Unbounded: A Generative Infinite Game of Character Life Simulation
Jialu Li, Yuanzhen Li, Neal Wadhwa +5
We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired b…
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion
Daniel Winter, Matan Cohen, Shlomi Fruchter +3
Diffusion models have revolutionized image editing but often generate images that violate physical laws, particularly the effects of objects on the scene, e.g., occlusions, shadows…
PALP: Prompt Aligned Personalization of Text-to-Image Models
Moab Arar, Andrey Voynov, Amir Hertz +5
Content creators often aim to create personalized images using personal subjects that go beyond the capabilities of conventional text-to-image models. Additionally, they may want t…
RealFill: Reference-Driven Generation for Authentic Image Completion
Luming Tang, Nataniel Ruiz, Qinghao Chu +8
Recent advances in generative imagery have brought forth outpainting and inpainting models that can produce high-quality, plausible image content in unknown regions. However, the c…
Computational Long Exposure Mobile Photography
Eric Tabellion, Nikhil Karnad, Noa Glaser +3
Long exposure photography produces stunning imagery, representing moving elements in a scene with motion-blur. It is generally employed in two modalities, producing either a foregr…
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
Nataniel Ruiz, Yuanzhen Li, Varun Jampani +6
Personalization has emerged as a prominent aspect within the field of generative AI, enabling the synthesis of individuals in diverse contexts and styles, while retaining high-fide…
Dreamix: Video Diffusion Models are General Video Editors
Eyal Molad, Eliahu Horwitz, Dani Valevski +5
Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very…
Null-text Inversion for Editing Real Images using Guided Diffusion Models
Ron Mokady, Amir Hertz, Kfir Aberman +2
Recent text-guided diffusion models provide powerful image generation capabilities. Currently, a massive effort is given to enable the modification of these images using text only…
Prompt-to-Prompt Image Editing with Cross Attention Control
Amir Hertz, Ron Mokady, Jay Tenenbaum +3
Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text pro…
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani +3
Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-quality and diverse synthesis of images from a given text prompt. However, these models…
MyStyle: A Personalized Generative Prior
Yotam Nitzan, Kfir Aberman, Qiurui He +6
We introduce MyStyle, a personalized deep generative prior trained with a few shots of an individual. MyStyle allows to reconstruct, enhance and edit images of a specific person, s…
Deep Saliency Prior for Reducing Visual Distraction
Kfir Aberman, Junfeng He, Yossi Gandelsman +5
Using only a model that was trained to predict where people look at images, and no additional training data, we can produce a range of powerful editing effects for reducing distrac…
Sky Optimization: Semantically aware image processing of skies in low-light photography
Orly Liba, Longqi Cai, Yun-Ta Tsai +5
The sky is a major component of the appearance of a photograph, and its color and tone can strongly influence the mood of a picture. In nighttime photography, the sky can also suff…
Handheld Mobile Photography in Very Low Light
Orly Liba, Kiran Murthy, Yun-Ta Tsai +10
Taking photographs in low light using a mobile phone is challenging and rarely produces pleasing results. Aside from the physical limits imposed by read noise and photon shot noise…
Synthetic Depth-of-Field with a Single-Camera Mobile Phone
Neal Wadhwa, Rahul Garg, David E. Jacobs +7
Shallow depth-of-field is commonly used by photographers to isolate a subject from a distracting background. However, standard cell phone cameras cannot produce such images optical…