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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 38 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2404.07448
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Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
Paper • 2310.03502 • Published • 77 -
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper • 2404.07448 • Published • 11 -
RegionGPT: Towards Region Understanding Vision Language Model
Paper • 2403.02330 • Published • 2 -
GLIGEN: Open-Set Grounded Text-to-Image Generation
Paper • 2301.07093 • Published • 3
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Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
Paper • 2310.03502 • Published • 77 -
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper • 2404.07448 • Published • 11 -
Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models
Paper • 2404.07973 • Published • 30 -
COCONut: Modernizing COCO Segmentation
Paper • 2404.08639 • Published • 27
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TextCraftor: Your Text Encoder Can be Image Quality Controller
Paper • 2403.18978 • Published • 13 -
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation
Paper • 2404.02733 • Published • 20 -
OmniFusion Technical Report
Paper • 2404.06212 • Published • 74 -
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper • 2404.07448 • Published • 11
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Demystifying CLIP Data
Paper • 2309.16671 • Published • 20 -
Model Stock: All we need is just a few fine-tuned models
Paper • 2403.19522 • Published • 10 -
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 20 -
On the Scalability of Diffusion-based Text-to-Image Generation
Paper • 2404.02883 • Published • 17
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Image Segmentation using U-Net Architecture for Powder X-ray Diffraction Images
Paper • 2310.16186 • Published • 2 -
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
Paper • 1709.07330 • Published • 2 -
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Paper • 1801.08599 • Published • 2 -
RTSeg: Real-time Semantic Segmentation Comparative Study
Paper • 1803.02758 • Published • 2
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Wide Residual Networks
Paper • 1605.07146 • Published • 2 -
Characterizing signal propagation to close the performance gap in unnormalized ResNets
Paper • 2101.08692 • Published • 2 -
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
Paper • 2105.03536 • Published • 2 -
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
Paper • 2106.01548 • Published • 2
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Simple Open-Vocabulary Object Detection with Vision Transformers
Paper • 2205.06230 • Published • 1 -
google/owlvit-base-patch32
Zero-Shot Object Detection • Updated • 626k • 123 -
Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers
Paper • 2305.07011 • Published • 5 -
Multi-Modal Classifiers for Open-Vocabulary Object Detection
Paper • 2306.05493 • Published • 6