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🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video reasoning tokens” to "reason" on physically plausible edits. See the attached... show more
37,032 görüntüleme • 11 ay önce •via X (Twitter)
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This work is a great collaboration at @NVIDIAAI by @jayzhangjiewu @xuanchi13 @TianchangS @TianshiC @Kai__He @YifanLu17525599 @ruiyuan_gao @xieenze_jr @voidrank Jose M. Alvarez @JunGao33210520 @FidlerSanja @zianwang97 @HuanLing6 Models and code will be released in the coming week. Stay Tuned.

1 - ChronoEdit repurposes pretrained video generative models for editing by reframing the task as a two-frame video generation problem, where the input image and its edited version are modeled as consecutive frames. When fine-tuned with curated image-editing data, this two-frame formulation equips the video model with editing functionalities while leveraging its pretrained temporal prior to preserve object fidelity.

3 - Overview of the ChronoEdit pipeline: From right to left, the denoising process begins in the temporal reasoning stage, where the model imagines and denoises a short trajectory of intermediate frames. These intermediate frames act as reasoning tokens, guiding how the edit should unfold in a physically consistent manner. For efficiency, the reasoning tokens are discarded in the subsequent editing frame generation stage, where the target frame is further refined into the final edited image.

2 - ChronoEdit introduces temporal reasoning toekns. If the video reasoning tokens are fully denoised into a clean video, the model can illustrate how it “thinks” by visualizing intermediate frames as a reasoning trajectory—though at the expense of slower inference. Notably, an emergent capability of our approach is its ability to generate reasoning trajectory videos to realize edits. Some interesting reasoning videos ( See more on project page).

Most reasonable diffusion image reasoning.

the vibes. what were some of the wildest failures y'all encountered?
