571 citations · 929 across the 39 of their papers we have counts for
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FreeSliders: Training-Free, Modality-Agnostic Concept Sliders for Fine-Grained Diffusion Control in Images, Audio, and Video
Rotem Ezra, Hedi Zisling, Nimrod Berman +5
Diffusion models have become state-of-the-art generative models for images, audio, and video, yet enabling fine-grained controllable generation, i.e., continuously steering specifi…
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Shelly Sheynin, Oron Ashual, Adam Polyak +4
Recent text-to-image models have achieved impressive results. However, since they require large-scale datasets of text-image pairs, it is impractical to train them on new domains w…
SegDiff: Image Segmentation with Diffusion Probabilistic Models
Tomer Amit, Tal Shaharbany, Eliya Nachmani +1
Diffusion Probabilistic Methods are employed for state-of-the-art image generation. In this work, we present a method for extending such models for performing image segmentation. T…