Rich feature hierarchies for accurate object detection and semantic segmentation
Paper • 1311.2524 • Published • 1
CV Papers
Computer Vision papers 👓
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DeepPose: Human Pose Estimation via Deep Neural Networks
Paper • 1312.4659 • Published • 1 -
Generative Adversarial Networks
Paper • 1406.2661 • Published • 5 -
scikit-image: Image processing in Python
Paper • 1407.6245 • Published • 1 -
ImageNet Large Scale Visual Recognition Challenge
Paper • 1409.0575 • Published • 10 -
Very Deep Convolutional Networks for Large-Scale Image Recognition
Paper • 1409.1556 • Published • 3 -
Going Deeper with Convolutions
Paper • 1409.4842 • Published • 2 -
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Paper • 1412.7062 • Published • 1 -
U-Net: Convolutional Networks for Biomedical Image Segmentation
Paper • 1505.04597 • Published • 18 -
You Only Look Once: Unified, Real-Time Object Detection
Paper • 1506.02640 • Published • 3 -
Deep Residual Learning for Image Recognition
Paper • 1512.03385 • Published • 16 -
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Paper • 1602.07360 • Published • 1 -
Identity Mappings in Deep Residual Networks
Paper • 1603.05027 • Published • 5 -
Densely Connected Convolutional Networks
Paper • 1608.06993 • Published • 4 -
Xception: Deep Learning with Depthwise Separable Convolutions
Paper • 1610.02357 • Published • 1 -
Image-to-Image Translation with Conditional Adversarial Networks
Paper • 1611.07004 • Published • 2 -
YOLO9000: Better, Faster, Stronger
Paper • 1612.08242 • Published • 3 -
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Paper • 1703.10593 • Published • 2 -
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Paper • 1704.04861 • Published • 1 -
A Style-Based Generator Architecture for Generative Adversarial Networks
Paper • 1812.04948 • Published • 3 -
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
Paper • 1812.08008 • Published • 1 -
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper • 1905.11946 • Published • 4 -
Deep High-Resolution Representation Learning for Visual Recognition
Paper • 1908.07919 • Published • 2 -
End-to-End Object Detection with Transformers
Paper • 2005.12872 • Published • 7 -
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Paper • 2010.11929 • Published • 15 -
Learning Transferable Visual Models From Natural Language Supervision
Paper • 2103.00020 • Published • 21 -
Vision Transformers for Dense Prediction
Paper • 2103.13413 • Published • 1 -
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Paper • 2103.14030 • Published • 5 -
Emerging Properties in Self-Supervised Vision Transformers
Paper • 2104.14294 • Published • 4 -
Elucidating the Design Space of Diffusion-Based Generative Models
Paper • 2206.00364 • Published • 18 -
Score-Based Generative Modeling through Stochastic Differential Equations
Paper • 2011.13456 • Published • 2 -
Mixture of Diffusers for scene composition and high resolution image generation
Paper • 2302.02412 • Published • 1 -
Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation
Paper • 2406.02347 • Published • 3 -
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
Paper • 2402.14167 • Published • 11 -
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Paper • 2211.01324 • Published • 4 -
Prompt-to-Prompt Image Editing with Cross Attention Control
Paper • 2208.01626 • Published • 3 -
FreeU: Free Lunch in Diffusion U-Net
Paper • 2309.11497 • Published • 66 -
Depth Anything V2
Paper • 2406.09414 • Published • 103 -
Make It Count: Text-to-Image Generation with an Accurate Number of Objects
Paper • 2406.10210 • Published • 78 -
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Paper • 2403.03206 • Published • 71 -
Consistency Models
Paper • 2303.01469 • Published • 8 -
aMUSEd: An Open MUSE Reproduction
Paper • 2401.01808 • Published • 31 -
Common Diffusion Noise Schedules and Sample Steps are Flawed
Paper • 2305.08891 • Published • 14 -
ControlNet-XS: Designing an Efficient and Effective Architecture for Controlling Text-to-Image Diffusion Models
Paper • 2312.06573 • Published • 1 -
Imagine yourself: Tuning-Free Personalized Image Generation
Paper • 2409.13346 • Published • 69 -
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Paper • 2208.01618 • Published • 2 -
Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models
Paper • 2409.10695 • Published • 3 -
Wasserstein GAN
Paper • 1701.07875 • Published • 1 -
Conditional Generative Adversarial Nets
Paper • 1411.1784 • Published • 1 -
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Paper • 1511.06434 • Published • 2 -
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Paper • 1609.04802 • Published • 1 -
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
Paper • 2305.10973 • Published • 39 -
Autoregressive Image Generation without Vector Quantization
Paper • 2406.11838 • Published • 5 -
CLIPAway: Harmonizing Focused Embeddings for Removing Objects via Diffusion Models
Paper • 2406.09368 • Published • 1