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Found 7 papers, 7 papers with code
DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing
Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years.
Deep Physics-Guided Unrolling Generalization for Compressed Sensing
By absorbing the merits of both the model- and data-driven methods, deep physics-engaged learning scheme achieves high-accuracy and interpretable image reconstruction.
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Specifically, we construct classifier guidance based on the strong correspondence of intermediate features in the diffusion model.
Dynamic Path-Controllable Deep Unfolding Network for Compressive Sensing
Deep unfolding network (DUN) that unfolds the optimization algorithm into a deep neural network has achieved great success in compressive sensing (CS) due to its good interpretability and high performance.
Optimization-Inspired Cross-Attention Transformer for Compressive Sensing
And, PGCA block achieves an enhanced information interaction, which introduces the inertia force into the gradient descent step through a cross attention block.
Large-capacity and Flexible Video Steganography via Invertible Neural Network
For large-capacity, we present a reversible pipeline to perform multiple videos hiding and recovering through a single invertible neural network (INN).
Memory-Augmented Deep Unfolding Network for Compressive Sensing
By understanding DUNs from the perspective of the human brain's memory processing, we find there exists two issues in existing DUNs.
