{"total":264,"rows":[{"id":"2112.03126","title":"Label-Efficient Semantic Segmentation with Diffusion Models","created":"2021-12-06","cited_by_count":499,"area":"diffusion"},{"id":"2209.11163","title":"GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images","created":"2022-09-22","cited_by_count":446,"area":null},{"id":"2306.03881","title":"Emergent Correspondence from Image Diffusion","created":"2023-06-06","cited_by_count":446,"area":"diffusion"},{"id":"2203.03570","title":"Kubric: A scalable dataset generator","created":"2022-03-07","cited_by_count":381,"area":null},{"id":"2303.04803","title":"Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models","created":"2023-03-08","cited_by_count":375,"area":"diffusion"},{"id":"2310.17596","title":"MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations","created":"2023-10-26","cited_by_count":327,"area":"offlinerl"},{"id":"2210.07574","title":"Is synthetic data from generative models ready for image recognition?","created":"2022-10-14","cited_by_count":320,"area":null},{"id":"2303.16203","title":"Your Diffusion Model is Secretly a Zero-Shot Classifier","created":"2023-03-28","cited_by_count":306,"area":"diffusion"},{"id":"2302.07944","title":"Effective Data Augmentation With Diffusion Models","created":"2023-02-07","cited_by_count":283,"area":"diffusion"},{"id":"2111.13587","title":"Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers","created":"2021-11-24","cited_by_count":248,"area":null},{"id":"2305.10973","title":"Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold","created":"2023-05-18","cited_by_count":219,"area":null},{"id":"2303.11681","title":"DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models","created":"2023-03-21","cited_by_count":162,"area":"diffusion"},{"id":"2111.03186","title":"EditGAN: High-Precision Semantic Image Editing","created":"2021-11-04","cited_by_count":156,"area":null},{"id":"2303.11306","title":"Localizing Object-level Shape Variations with Text-to-Image Diffusion Models","created":"2023-03-20","cited_by_count":142,"area":"diffusion"},{"id":"2308.06160","title":"DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models","created":"2023-08-11","cited_by_count":123,"area":"diffusion"},{"id":"2206.10207","title":"SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders","created":"2022-06-21","cited_by_count":114,"area":null},{"id":"2309.14303","title":"Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation","created":"2023-09-25","cited_by_count":112,"area":null},{"id":"2106.05258","title":"Generative Models as a Data Source for Multiview Representation Learning","created":"2021-06-09","cited_by_count":104,"area":null},{"id":"2305.16289","title":"Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation","created":"2023-05-25","cited_by_count":100,"area":null},{"id":"2310.07849","title":"Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations","created":"2023-10-11","cited_by_count":100,"area":"synth"},{"id":"2201.04684","title":"BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations","created":"2022-01-12","cited_by_count":99,"area":null},{"id":"2308.10916","title":"Diffusion Model as Representation Learner","created":"2023-08-21","cited_by_count":95,"area":"diffusion"},{"id":"2106.05963","title":"Learning to See by Looking at Noise","created":"2021-06-10","cited_by_count":92,"area":null},{"id":"2112.05219","title":"CLIP2StyleGAN: Unsupervised Extraction of StyleGAN Edit Directions","created":"2021-12-09","cited_by_count":78,"area":null},{"id":"2204.07513","title":"Synthesizing Informative Training Samples with GAN","created":"2022-04-15","cited_by_count":77,"area":null},{"id":"2311.10091","title":"Adaptive Shells for Efficient Neural Radiance Field Rendering","created":"2023-11-16","cited_by_count":69,"area":null},{"id":"2110.08398","title":"Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks","created":"2021-10-15","cited_by_count":68,"area":null},{"id":"2305.02310","title":"Real-Time Radiance Fields for Single-Image Portrait View Synthesis","created":"2023-05-03","cited_by_count":64,"area":null},{"id":"2112.05143","title":"GAN-Supervised Dense Visual Alignment","created":"2021-12-09","cited_by_count":62,"area":null},{"id":"2211.13976","title":"Expanding Small-Scale Datasets with Guided Imagination","created":"2022-11-25","cited_by_count":62,"area":null},{"id":"2310.15160","title":"FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models","created":"2023-10-23","cited_by_count":61,"area":null},{"id":"2111.06349","title":"Unsupervised Part Discovery from Contrastive Reconstruction","created":"2021-11-11","cited_by_count":57,"area":null},{"id":"2303.09813","title":"DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery","created":"2023-03-17","cited_by_count":54,"area":"diffusion"},{"id":"2111.00140","title":"DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer","created":"2021-10-30","cited_by_count":52,"area":null},{"id":"2311.17137","title":"Generative Models: What Do They Know? Do They Know Things? Let's Find Out!","created":"2023-11-28","cited_by_count":50,"area":"diffusion"},{"id":"2312.03048","title":"DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control","created":"2023-12-05","cited_by_count":45,"area":"diffusion"},{"id":"2306.00987","title":"StyleGAN knows Normal, Depth, Albedo, and More","created":"2023-06-01","cited_by_count":44,"area":null},{"id":"2401.11739","title":"EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models","created":"2024-01-22","cited_by_count":43,"area":"diffusion"},{"id":"2403.16605","title":"SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation","created":"2024-03-25","cited_by_count":41,"area":"diffusion"},{"id":"2302.10586","title":"Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels","created":"2023-02-21","cited_by_count":37,"area":"diffusion"},{"id":"2307.07487","title":"DreamTeacher: Pretraining Image Backbones with Deep Generative Models","created":"2023-07-14","cited_by_count":37,"area":null},{"id":"2310.10402","title":"Real-Fake: Effective Training Data Synthesis Through Distribution Matching","created":"2023-10-16","cited_by_count":36,"area":null},{"id":"2309.13042","title":"MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation","created":"2023-09-22","cited_by_count":35,"area":"diffusion"},{"id":"2202.14020","title":"State-of-the-Art in the Architecture, Methods and Applications of StyleGAN","created":"2022-02-28","cited_by_count":34,"area":null},{"id":"2306.07200","title":"Fill-Up: Balancing Long-Tailed Data with Generative Models","created":"2023-06-12","cited_by_count":34,"area":null},{"id":"2203.15799","title":"StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis","created":"2022-03-29","cited_by_count":33,"area":null},{"id":"2311.17921","title":"Do text-free diffusion models learn discriminative visual representations?","created":"2023-11-29","cited_by_count":33,"area":"diffusion"},{"id":"2204.06504","title":"DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization","created":"2022-04-13","cited_by_count":32,"area":null},{"id":"2401.12978","title":"Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models","created":"2024-01-23","cited_by_count":32,"area":"diffusion"},{"id":"2203.09301","title":"One-Shot Adaptation of GAN in Just One CLIP","created":"2022-03-17","cited_by_count":31,"area":null},{"id":"2308.03977","title":"PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning","created":"2023-08-08","cited_by_count":31,"area":null},{"id":"2203.10821","title":"Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields","created":"2022-03-21","cited_by_count":29,"area":null},{"id":"2303.12343","title":"LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation","created":"2023-03-22","cited_by_count":29,"area":"diffusion"},{"id":"2208.12408","title":"User-Controllable Latent Transformer for StyleGAN Image Layout Editing","created":"2022-08-26","cited_by_count":28,"area":null},{"id":"2410.14987","title":"SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning","created":"2024-10-19","cited_by_count":27,"area":null},{"id":"2106.04823","title":"Taxonomy of Machine Learning Safety: A Survey and Primer","created":"2021-06-09","cited_by_count":25,"area":null},{"id":"2304.02163","title":"GINA-3D: Learning to Generate Implicit Neural Assets in the Wild","created":"2023-04-04","cited_by_count":25,"area":null},{"id":"2212.07409","title":"Self-Supervised Geometry-Aware Encoder for Style-Based 3D GAN Inversion","created":"2022-12-14","cited_by_count":24,"area":null},{"id":"2302.08509","title":"3D-aware Conditional Image Synthesis","created":"2023-02-16","cited_by_count":24,"area":null},{"id":"2312.09231","title":"Reliability in Semantic Segmentation: Can We Use Synthetic Data?","created":"2023-12-14","cited_by_count":24,"area":null},{"id":"2403.12803","title":"DreamDA: Generative Data Augmentation with Diffusion Models","created":"2024-03-19","cited_by_count":24,"area":"diffusion"},{"id":"2203.11105","title":"High-fidelity GAN Inversion with Padding Space","created":"2022-03-21","cited_by_count":23,"area":null},{"id":"2202.09649","title":"Region-Based Semantic Factorization in GANs","created":"2022-02-19","cited_by_count":22,"area":null},{"id":"2312.03763","title":"Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing","created":"2023-12-05","cited_by_count":22,"area":null},{"id":"2107.12518","title":"Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP","created":"2021-07-26","cited_by_count":21,"area":null},{"id":"2207.09855","title":"Everything is There in Latent Space: Attribute Editing and Attribute Style Manipulation by StyleGAN Latent Space Exploration","created":"2022-07-20","cited_by_count":21,"area":null},{"id":"2205.11423","title":"Decoder Denoising Pretraining for Semantic Segmentation","created":"2022-05-23","cited_by_count":20,"area":null},{"id":"2403.06741","title":"Distribution-Aware Data Expansion with Diffusion Models","created":"2024-03-11","cited_by_count":20,"area":"diffusion"},{"id":"2409.20562","title":"SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes","created":"2024-09-30","cited_by_count":20,"area":null},{"id":"2112.01036","title":"GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation","created":"2021-12-02","cited_by_count":19,"area":null},{"id":"2301.00954","title":"PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation","created":"2023-01-03","cited_by_count":19,"area":null},{"id":"2308.12288","title":"CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images","created":"2023-08-23","cited_by_count":19,"area":null},{"id":"2212.02024","title":"Fine-grained Image Editing by Pixel-wise Guidance Using Diffusion Models","created":"2022-12-05","cited_by_count":18,"area":"diffusion"},{"id":"2311.03355","title":"SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis","created":"2023-11-06","cited_by_count":18,"area":null},{"id":"2401.05906","title":"PartSTAD: 2D-to-3D Part Segmentation Task Adaptation","created":"2024-01-11","cited_by_count":18,"area":null},{"id":"2203.16521","title":"CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs","created":"2022-03-30","cited_by_count":17,"area":null},{"id":"2405.15199","title":"ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models","created":"2024-05-24","cited_by_count":17,"area":"diffusion"},{"id":"2202.02713","title":"FEAT: Face Editing with Attention","created":"2022-02-06","cited_by_count":16,"area":null},{"id":"2306.08964","title":"Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification","created":"2023-06-15","cited_by_count":16,"area":"diffusion"},{"id":"2210.13835","title":"Synthetic Data Supervised Salient Object Detection","created":"2022-10-25","cited_by_count":15,"area":null},{"id":"2301.04604","title":"LinkGAN: Linking GAN Latents to Pixels for Controllable Image Synthesis","created":"2023-01-11","cited_by_count":15,"area":null},{"id":"2309.07698","title":"Dataset Condensation via Generative Model","created":"2023-09-14","cited_by_count":15,"area":null},{"id":"2405.10185","title":"DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data","created":"2024-05-16","cited_by_count":15,"area":null},{"id":"2406.01264","title":"FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor Synthesis","created":"2024-06-03","cited_by_count":15,"area":null},{"id":"2409.14066","title":"KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data","created":"2024-09-21","cited_by_count":15,"area":"mllm"},{"id":"2412.18947","title":"MedHallBench: A New Benchmark for Assessing Hallucination in Medical Large Language Models","created":"2024-12-25","cited_by_count":15,"area":null},{"id":"2504.12080","title":"DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency","created":"2025-04-16","cited_by_count":15,"area":null},{"id":"2202.08937","title":"When, Why, and Which Pretrained GANs Are Useful?","created":"2022-02-17","cited_by_count":14,"area":null},{"id":"2305.10722","title":"Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners","created":"2023-05-18","cited_by_count":14,"area":"diffusion"},{"id":"2403.12852","title":"Generative Enhancement for 3D Medical Images","created":"2024-03-19","cited_by_count":14,"area":"diffusion"},{"id":"2509.17431","title":"Hierarchical Neural Semantic Representation for 3D Semantic Correspondence","created":"2025-09-22","cited_by_count":14,"area":null},{"id":"2112.00854","title":"GANORCON: Are Generative Models Useful for Few-shot Segmentation?","created":"2021-12-01","cited_by_count":13,"area":null},{"id":"2302.06608","title":"3D-aware Blending with Generative NeRFs","created":"2023-02-13","cited_by_count":13,"area":null},{"id":"2308.00994","title":"SYNAuG: Exploiting Synthetic Data for Data Imbalance Problems","created":"2023-08-02","cited_by_count":13,"area":null},{"id":"2310.01830","title":"AI-Generated Images as Data Source: The Dawn of Synthetic Era","created":"2023-10-03","cited_by_count":13,"area":null},{"id":"2403.06168","title":"DiffuMatting: Synthesizing Arbitrary Objects with Matting-level Annotation","created":"2024-03-10","cited_by_count":13,"area":null},{"id":"2407.05352","title":"Exploring Phrase-Level Grounding with Text-to-Image Diffusion Model","created":"2024-07-07","cited_by_count":13,"area":"diffusion"},{"id":"2111.07971","title":"Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation","created":"2021-11-15","cited_by_count":12,"area":null},{"id":"2305.12799","title":"Interactive Data Synthesis for Systematic Vision Adaptation via LLMs-AIGCs Collaboration","created":"2023-05-22","cited_by_count":12,"area":"synth"},{"id":"2308.12380","title":"FG-Net: Facial Action Unit Detection with Generalizable Pyramidal Features","created":"2023-08-23","cited_by_count":12,"area":null}],"next_cursor":"100"}