深度学习 · generative models and autoencoders论文趋势 2023–2026

主要结论

• 深度学习 · generative models and autoencoders论文从 2023 年的 1,216 篇增长到 2026 年的 1,430 篇，三年间扩大到约 1.2 倍。
• NeurIPS 是发深度学习 · generative models and autoencoders论文最多的会议，2023–2026 年共 1,714 篇，占四个会议总量的 40%。
• 交叉方向里涨得最快的是图像生成：同时属于两个主题的论文从 2023 年的 35 篇增至 2026 年的 150 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 2；同组增长最快的扩散模型是 4.1 倍，深度学习 · generative models and autoencoders是 1.2 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026A Critical $\beta$-Scale for Posterior Collapse in Dirichlet $\beta$-VAEs
• ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
• ICLR 2026``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood
• CVPR 2026Anchoring and Rescaling Attention for Semantically Coherent Inbetweening
• NeurIPS 2025Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
• ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
• ICLR 2025A Watermark for Order-Agnostic Language Models
• CVPR 2025DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Fixed-Point Approach for Causal Generative Modeling
• ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
• CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
• NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
• ICML 2023A Kernelized Stein Discrepancy for Biological Sequences
• ICLR 2023Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
• CVPR 20233D GAN Inversion With Facial Symmetry Prior
• NeurIPS 2026Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
• ICML 2026$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
• ICLR 2026Analyzing and Evaluating Unbiased Language Model Watermark
• CVPR 2026Bidirectional Normalizing Flow From Data to Noise and Back

全部深度学习 · generative models and autoencoders论文

共 900 篇，第 2 / 18 页

51. CVPR 2025Generative Video Propagation
52. CVPR 2025GENIUS: A Generative Framework for Universal Multimodal Search
53. CVPR 2025GenPC: Zero-shot Point Cloud Completion via 3D Generative Priors
54. CVPR 2025GIF: Generative Inspiration for Face Recognition at Scale
55. CVPR 2025Goku: Flow Based Video Generative Foundation Models
56. CVPR 2025Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion
57. CVPR 2025GraphMimic: Graph-to-Graphs Generative Modeling from Videos for Policy Learning
58. CVPR 2025HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
59. CVPR 2025IceDiff: High Resolution and High-Quality Arctic Sea Ice Forecasting with Generative Diffusion Prior
60. CVPR 2025IDEA-Bench: How Far are Generative Models from Professional Designing?
61. CVPR 2025Interpretable Generative Models through Post-hoc Concept Bottlenecks
62. CVPR 2025K-LoRA: Unlocking Training-Free Fusion of Any Subject and Style LoRAs
63. CVPR 2025K-Sort Arena: Efficient and Reliable Benchmarking for Generative Models via K-wise Human Preferences
64. CVPR 2025Learning Visual Generative Priors without Text
65. CVPR 2025LookingGlass: Generative Anamorphoses via Laplacian Pyramid Warping
66. CVPR 2025LT3SD: Latent Trees for 3D Scene Diffusion
67. CVPR 2025LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting
68. CVPR 2025MARBLE: Material Recomposition and Blending in CLIP-Space
69. CVPR 2025MEGA: Masked Generative Autoencoder for Human Mesh Recovery
70. CVPR 2025MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos
71. CVPR 2025MeshGen: Generating PBR Textured Mesh with Render-Enhanced Auto-Encoder and Generative Data Augmentation
72. CVPR 2025MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors
73. CVPR 2025NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images
74. CVPR 2025ObjectMover: Generative Object Movement with Video Prior
75. CVPR 2025Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding
76. CVPR 2025Omni-ID: Holistic Identity Representation Designed for Generative Tasks
77. CVPR 2025OSDFace: One-Step Diffusion Model for Face Restoration
78. CVPR 2025ParaHome: Parameterizing Everyday Home Activities Towards 3D Generative Modeling of Human-Object Interactions
79. CVPR 2025PERSE: Personalized 3D Generative Avatars from A Single Portrait
80. CVPR 2025Perturb-and-Revise: Flexible 3D Editing with Generative Trajectories
81. CVPR 2025PhysAnimator: Physics-Guided Generative Cartoon Animation
82. CVPR 2025PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?
83. CVPR 2025POMP: Physics-consistent Motion Generative Model through Phase Manifolds
84. CVPR 2025PSHuman: Photorealistic Single-image 3D Human Reconstruction using Cross-Scale Multiview Diffusion and Explicit Remeshing
85. CVPR 2025Revisiting Generative Replay for Class Incremental Object Detection
86. CVPR 2025RICCARDO: Radar Hit Prediction and Convolution for Camera-Radar 3D Object Detection
87. CVPR 2025RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins
88. CVPR 2025SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model
89. CVPR 2025Segment Any-Quality Images with Generative Latent Space Enhancement
90. CVPR 2025SF3D: Stable Fast 3D Mesh Reconstruction with UV-unwrapping and Illumination Disentanglement
91. CVPR 2025ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion
92. CVPR 2025Shining Yourself: High-Fidelity Ornaments Virtual Try-on with Diffusion Model
93. CVPR 2025Symbolic Representation for Any-to-Any Generative Tasks
94. CVPR 2025Temporal Score Analysis for Understanding and Correcting Diffusion Artifacts
95. CVPR 2025Tiled Diffusion
96. CVPR 2025Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
97. CVPR 2025Towards Smart Point-and-Shoot Photography
98. CVPR 2025Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training?
99. CVPR 2025Traversing Distortion-Perception Tradeoff using a Single Score-Based Generative Model
100. CVPR 2025UnCommon Objects in 3D

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · generative models and autoencoders论文？

共 4,314 篇，按年份分别是 2023 年 1,216 篇、2024 年 768 篇、2025 年 900 篇、2026 年 1,430 篇。

NeurIPS 2026 有多少篇深度学习 · generative models and autoencoders论文？

NeurIPS 2026 有 349 篇深度学习 · generative models and autoencoders论文，上一届是 240 篇。

ICLR 2026 有多少篇深度学习 · generative models and autoencoders论文？

ICLR 2026 有 303 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。

ICML 2026 有多少篇深度学习 · generative models and autoencoders论文？

ICML 2026 有 604 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。

CVPR 2026 有多少篇深度学习 · generative models and autoencoders论文？

CVPR 2026 有 174 篇深度学习 · generative models and autoencoders论文，上一届是 110 篇。

哪个会议的深度学习 · generative models and autoencoders论文最多？

NeurIPS，2023–2026 年共 1,714 篇。