{"list":"other","total":66,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"1801.03924","title":"The Unreasonable Effectiveness of Deep Features as a Perceptual Metric","created":"2018-01-11","cited_by_count":11177},{"id":"2010.02502","title":"Denoising Diffusion Implicit Models","created":"2020-10-06","cited_by_count":9781},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255},{"id":"1503.03585","title":"Deep Unsupervised Learning using Nonequilibrium Thermodynamics","created":"2015-03-12","cited_by_count":7058},{"id":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"1907.05600","title":"Generative Modeling by Estimating Gradients of the Data Distribution","created":"2019-07-12","cited_by_count":4101},{"id":"1411.7766","title":"Deep Learning Face Attributes in the Wild","created":"2014-11-28","cited_by_count":3693},{"id":"2012.09841","title":"Taming Transformers for High-Resolution Image Synthesis","created":"2020-12-17","cited_by_count":3253},{"id":"2206.00364","title":"Elucidating the Design Space of Diffusion-Based Generative Models","created":"2022-06-01","cited_by_count":3045},{"id":"1703.06868","title":"Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization","created":"2017-03-20","cited_by_count":2010},{"id":"2206.00927","title":"DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps","created":"2022-06-02","cited_by_count":1979},{"id":"1506.03365","title":"LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop","created":"2015-06-10","cited_by_count":1355},{"id":"1610.01644","title":"Understanding intermediate layers using linear classifier probes","created":"2016-10-05","cited_by_count":1353},{"id":"2107.00630","title":"Variational Diffusion Models","created":"2021-07-01","cited_by_count":1153},{"id":"2202.09778","title":"Pseudo Numerical Methods for Diffusion Models on Manifolds","created":"2022-02-20","cited_by_count":700},{"id":"2106.05931","title":"Score-based Generative Modeling in Latent Space","created":"2021-06-10","cited_by_count":636},{"id":"2004.02546","title":"GANSpace: Discovering Interpretable GAN Controls","created":"2020-04-06","cited_by_count":614},{"id":"2210.06978","title":"LION: Latent Point Diffusion Models for 3D Shape Generation","created":"2022-10-12","cited_by_count":553},{"id":"2204.13902","title":"Fast Sampling of Diffusion Models with Exponential Integrator","created":"2022-04-29","cited_by_count":532},{"id":"2302.04867","title":"UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models","created":"2023-02-09","cited_by_count":450},{"id":"2111.15640","title":"Diffusion Autoencoders: Toward a Meaningful and Decodable Representation","created":"2021-11-30","cited_by_count":449},{"id":"2301.11093","title":"Simple diffusion: End-to-end diffusion for high resolution images","created":"2023-01-26","cited_by_count":422},{"id":"2312.02696","title":"Analyzing and Improving the Training Dynamics of Diffusion Models","created":"2023-12-05","cited_by_count":402},{"id":"1609.03552","title":"Generative Visual Manipulation on the Natural Image Manifold","created":"2016-09-12","cited_by_count":348},{"id":"2210.10960","title":"Diffusion Models already have a Semantic Latent Space","created":"2022-10-20","cited_by_count":328},{"id":"2212.06135","title":"Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion","created":"2022-12-12","cited_by_count":309},{"id":"2204.00227","title":"Perception Prioritized Training of Diffusion Models","created":"2022-04-01","cited_by_count":303},{"id":"2112.07068","title":"Score-Based Generative Modeling with Critically-Damped Langevin Diffusion","created":"2021-12-14","cited_by_count":233},{"id":"2301.10972","title":"On the Importance of Noise Scheduling for Diffusion Models","created":"2023-01-26","cited_by_count":194},{"id":"2209.06950","title":"Lossy Image Compression with Conditional Diffusion Models","created":"2022-09-14","cited_by_count":170},{"id":"2209.08725","title":"Neural Wavelet-domain Diffusion for 3D Shape Generation","created":"2022-09-19","cited_by_count":132},{"id":"2401.11605","title":"Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers","created":"2024-01-21","cited_by_count":118},{"id":"2304.07060","title":"DCFace: Synthetic Face Generation with Dual Condition Diffusion Model","created":"2023-04-14","cited_by_count":116},{"id":"2201.00308","title":"DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents","created":"2022-01-02","cited_by_count":104},{"id":"2312.03701","title":"Return of Unconditional Generation: A Self-supervised Representation Generation Method","created":"2023-12-06","cited_by_count":98},{"id":"2311.17901","title":"SODA: Bottleneck Diffusion Models for Representation Learning","created":"2023-11-29","cited_by_count":77},{"id":"2304.06711","title":"DiffusionRig: Learning Personalized Priors for Facial Appearance Editing","created":"2023-04-13","cited_by_count":75},{"id":"2105.14257","title":"Diffusion-Based Representation Learning","created":"2021-05-29","cited_by_count":57},{"id":"2306.08757","title":"InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models","created":"2023-06-14","cited_by_count":50},{"id":"2303.17550","title":"DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder","created":"2023-03-30","cited_by_count":48},{"id":"2212.02802","title":"Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding","created":"2022-12-06","cited_by_count":39},{"id":"2401.11430","title":"Exploring Diffusion Time-steps for Unsupervised Representation Learning","created":"2024-01-21","cited_by_count":36},{"id":"2402.09712","title":"Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement","created":"2024-02-15","cited_by_count":27},{"id":"2407.03300","title":"DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents","created":"2024-07-03","cited_by_count":20},{"id":"2304.11829","title":"Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation","created":"2023-04-24","cited_by_count":18},{"id":"2404.17735","title":"Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models","created":"2024-04-27","cited_by_count":18},{"id":"2301.04218","title":"Leveraging Diffusion For Strong and High Quality Face Morphing Attacks","created":"2023-01-10","cited_by_count":14},{"id":"2403.17217","title":"DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment","created":"2024-03-25","cited_by_count":14},{"id":"2311.01811","title":"DiffDub: Person-generic Visual Dubbing Using Inpainting Renderer with Diffusion Auto-encoder","created":"2023-11-03","cited_by_count":10},{"id":"2404.06025","title":"Greedy-DiM: Greedy Algorithms for Unreasonably Effective Face Morphs","created":"2024-04-09","cited_by_count":10},{"id":"2402.02346","title":"Closed-Loop Unsupervised Representation Disentanglement with $\\beta$-VAE Distillation and Diffusion Probabilistic Feedback","created":"2024-02-04","cited_by_count":9},{"id":"2304.07429","title":"Identity Encoder for Personalized Diffusion","created":"2023-04-14","cited_by_count":8},{"id":"2405.17111","title":"Diffusion Bridge AutoEncoders for Unsupervised Representation Learning","created":"2024-05-27","cited_by_count":6},{"id":"2307.05899","title":"DiffuseGAE: Controllable and High-fidelity Image Manipulation from Disentangled Representation","created":"2023-07-12","cited_by_count":4},{"id":"2402.09137","title":"Semi-Supervised Diffusion Model for Brain Age Prediction","created":"2024-02-14","cited_by_count":4},{"id":"2404.13798","title":"Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation","created":"2024-04-21","cited_by_count":4},{"id":"2303.12031","title":"Semantic Latent Space Regression of Diffusion Autoencoders for Vertebral Fracture Grading","created":"2023-03-21","cited_by_count":2},{"id":"2404.08111","title":"S3Editor: A Sparse Semantic-Disentangled Self-Training Framework for Face Video Editing","created":"2024-04-11","cited_by_count":1}],"next_cursor":null}