Results 21 to 30 of about 24,691,873 (342)
LayoutDM: Discrete Diffusion Model for Controllable Layout Generation [PDF]
Computer Vision and Pattern Recognition, 2023 Controllable layout generation aims at synthesizing plausible arrangement of element bounding boxes with optional constraints, such as type or position of a specific element.
Naoto Inoue +4 more
semanticscholar +1 more source
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds [PDF]
Neural Information Processing Systems, 2023 Text-to-image diffusion models can create stunning images from natural language descriptions that rival the work of professional artists and photographers.
Yanyu Li +8 more
semanticscholar +1 more source
Classifier-Free Diffusion Guidance [PDF]
arXiv.org, 2022 Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as low temperature sampling or truncation in other types of generative models. Classifier
Jonathan Ho
semanticscholar +1 more source
High-Resolution Image Synthesis with Latent Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2021 By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a guiding mechanism
Robin Rombach +4 more
semanticscholar +1 more source
PhysDiff: Physics-Guided Human Motion Diffusion Model [PDF]
IEEE International Conference on Computer Vision, 2022 Denoising diffusion models hold great promise for generating diverse and realistic human motions. However, existing motion diffusion models largely disregard the laws of physics in the diffusion process and often generate physically-implausible motions ...
Ye Yuan +4 more
semanticscholar +1 more source
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps [PDF]
Neural Information Processing Systems, 2022 Diffusion probabilistic models (DPMs) are emerging powerful generative models. Despite their high-quality generation performance, DPMs still suffer from their slow sampling as they generally need hundreds or thousands of sequential function evaluations ...
Cheng Lu +5 more
semanticscholar +1 more source
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding [PDF]
Computer Vision and Pattern Recognition, 2022 Decoding visual stimuli from brain recordings aims to deepen our understanding of the human visual system and build a solid foundation for bridging human and computer vision through the Brain-Computer Interface.
Zijiao Chen +4 more
semanticscholar +1 more source
Applied Sciences, 2023 Agriculture is pivotal in national economies, with pest classification significantly influencing food quality and quantity. In recent years, pest classification methods based on deep learning have made progress. However, there are two problems with these
Tengyue Wu +5 more
doaj +1 more source
Remote Sensing, 2023 With the widespread application and functional complexity of deep neural networks (DNNs), the demand for training samples is increasing. This elevated requirement also extends to DNN-based SAR object detection.
Yi Kuang +4 more
doaj +1 more source
Exactly solvable model of quantum diffusion [PDF]
, 2004 We study the transport property of diffusion in a finite translationally invariant quantum subsystem described by a tight-binding Hamiltonian with a single energy band and interacting with its environment by a coupling in terms of correlation functions ...
A. Knauf +28 more
core +3 more sources