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Image Generation

ZipAR: Accelerating Autoregressive Image Generation through Spatial Locality
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Zhejiang University
ZipAR accelerates autoregressive image generation by up to 91% through parallel decoding leveraging spatial locality in images, making high-resolution image generation significantly faster.
SwiftEdit: Lightning Fast Text-Guided Image Editing via One-Step Diffusion
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 VinAI Research
SwiftEdit achieves lightning-fast, high-quality text-guided image editing in just 0.23 seconds via a novel one-step diffusion process.
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 ByteDance
Infinity, a novel bitwise autoregressive model, sets new records in high-resolution image synthesis, outperforming top diffusion models in speed and quality.
HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editing
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Peking University
HumanEdit: A new human-rewarded dataset revolutionizes instruction-based image editing by providing high-quality, diverse image pairs with detailed instructions, enabling precise model evaluation and …
Hidden in the Noise: Two-Stage Robust Watermarking for Images
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 New York University
WIND: A novel, distortion-free image watermarking method leveraging diffusion models’ initial noise for robust AI-generated content authentication.
AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent Diffusion Models
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 ByteDance
AnyDressing: Customizable multi-garment virtual dressing via a novel latent diffusion model!
NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Tencent AI Lab
NVComposer: A novel generative NVS model boosts synthesis quality by implicitly inferring spatial relationships from multiple sparse, unposed images, eliminating reliance on external alignment.
MV-Adapter: Multi-view Consistent Image Generation Made Easy
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 School of Software, Beihang University
MV-Adapter easily transforms existing image generators into multi-view consistent image generators, improving efficiency and adaptability.
Imagine360: Immersive 360 Video Generation from Perspective Anchor
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Chinese University of Hong Kong
Imagine360: Generating immersive 360Β° videos from perspective videos, improving quality and accessibility of 360Β° content creation.
CleanDIFT: Diffusion Features without Noise
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 CompVis @ LMU Munich, MCML
CleanDIFT revolutionizes diffusion feature extraction by leveraging clean images and a lightweight fine-tuning method, significantly boosting performance across various tasks without noise or timestep…
SNOOPI: Supercharged One-step Diffusion Distillation with Proper Guidance
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 VinAI Research
SNOOPI supercharges one-step diffusion model distillation with enhanced guidance, achieving state-of-the-art performance by stabilizing training and enabling negative prompt control.
Scaling Image Tokenizers with Grouped Spherical Quantization
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 JΓΌlich Supercomputing Centre
GSQ-GAN, a novel image tokenizer, achieves superior reconstruction quality with 16x downsampling using grouped spherical quantization, enabling efficient scaling for high-fidelity image generation.
TinyFusion: Diffusion Transformers Learned Shallow
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 National University of Singapore
TinyFusion, a novel learnable depth pruning method, crafts efficient shallow diffusion transformers with superior post-fine-tuning performance, achieving a 2x speedup with less than 7% of the original…
Switti: Designing Scale-Wise Transformers for Text-to-Image Synthesis
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Yandex Research
SWITTI: a novel scale-wise transformer achieves 7x faster text-to-image generation than state-of-the-art diffusion models, while maintaining competitive image quality.
NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 SketchX, CVSSP, University of Surrey
NitroFusion achieves high-fidelity single-step image generation using a dynamic adversarial training approach with a specialized discriminator pool, dramatically improving speed and quality.
Negative Token Merging: Image-based Adversarial Feature Guidance
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 University of Washington
NegToMe: Image-based adversarial guidance improves image generation diversity and reduces similarity to copyrighted content without training, simply by using images instead of negative text prompts.
Open-Sora Plan: Open-Source Large Video Generation Model
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Peking University
Open-Sora Plan introduces an open-source large video generation model capable of producing high-resolution videos with long durations, based on various user inputs.
TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Machine Learning Group, CITEC, Bielefeld University
TryOffDiff generates realistic garment images from single photos, solving virtual try-on limitations.
ROICtrl: Boosting Instance Control for Visual Generation
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 Show Lab, National University of Singapore
ROICtrl boosts visual generation’s instance control by using regional instance control via ROI-Align and a new ROI-Unpool operation, resulting in precise regional control and high efficiency.
FAM Diffusion: Frequency and Attention Modulation for High-Resolution Image Generation with Stable Diffusion
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AI Generated πŸ€— Daily Papers Computer Vision Image Generation 🏒 University of Cambridge
FAM Diffusion: Generate high-res images seamlessly from pre-trained diffusion models, solving structural and texture inconsistencies without retraining!