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Found 6 papers, 3 papers with code
ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback
To this end, we propose ControlNet++, a novel approach that improves controllable generation by explicitly optimizing pixel-level cycle consistency between generated images and conditional controls.
UniFL: Improve Stable Diffusion via Unified Feedback Learning
Diffusion models have revolutionized the field of image generation, leading to the proliferation of high-quality models and diverse downstream applications.
ByteEdit: Boost, Comply and Accelerate Generative Image Editing
Recent advancements in diffusion-based generative image editing have sparked a profound revolution, reshaping the landscape of image outpainting and inpainting tasks.
DLIP: Distilling Language-Image Pre-training
Furthermore, DLIP succeeds in retaining more than 95% of the performance with 22. 4% parameters and 24. 8% FLOPs compared to the teacher model and accelerates inference speed by 2. 7x.
Latent Feature Relation Consistency for Adversarial Robustness
Deep neural networks have been applied in many computer vision tasks and achieved state-of-the-art performance.
CAT:Collaborative Adversarial Training
By revisiting the previous methods, we find different adversarial training methods have distinct robustness for sample instances.
