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Works32 from public data
- MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing902
MasaCtrl converts existing self-attention in diffusion models into mutual self-attention, so that it can query correlated local contents and textures from source images for consistency, and proposes a mask-guided mutual self-attention strategy.
- MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment864
Multi-dimension Attention Network for no-reference Image Quality Assessment (MANIQA) is proposed to improve the performance on GAN-based distortion images and outperforms state-of-the-art methods on four standard datasets by a large margin.
- PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding410
PhotoMaker is introduced, an efficient personalized text-to-image generation method, which mainly encodes an arbitrary number of input ID images into a stack ID embed-ding for preserving ID information, and an ID-oriented data construction pipeline to assemble the training data.
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- VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control98
This work proposes VideoPainter, an efficient dual-branch framework featuring a lightweight context encoder that processes masked videos and injects background guidance into any pre-trained video diffusion transformer, generalizing across arbitrary mask types, enhancing background integration and foreground generation, and enabling user-customized control.
- NTIRE 2022 Challenge on Perceptual Image Quality Assessment84
This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022 to address the emerging challenge of IQA by perceptual image processing algorithms.
- VDTR: Video Deblurring With Transformer68
VDTR is an effective Transformer-based model that makes the first attempt to adapt pure Transformer for video deblurring, and achieves highly competitive results on both synthetic and real-world videodeblurring benchmarks, including DVD, GOPRO, REDS and BSD.
- Blur Interpolation Transformer for Real-World Motion from Blur62
A blur interpolation transformer (BiT) is proposed to effectively unravel the underlying temporal correlation encoded in blur to generate effective features for time-varying motion rendering and a hybrid camera system is designed to collect the first real-world dataset of one-to-many blur-sharp video pairs.
- NTIRE 2021 Challenge on Perceptual Image Quality Assessment55
The NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021, achieved much better results than existing IQA methods, while the winning method can demonstrate state-of-the-art performance.
- OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer48
This paper designs a distortion-aware Transformer (OSRT) to modulate ERP distortions continuously and self-adaptively, and proposes Fisheye downsampling, which mimics the real-world imaging process and synthesizes more realistic low-resolution samples.
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- Region-Adaptive Deformable Network for Image Quality Assessment36
The referenceoriented deformable convolution is proposed, which can improve the performance of an IQA network on GAN-based distortion by adaptively considering this misalignment and a patch-level attention module to enhance the interaction among different patch regions, which are processed independently in previous patch-based methods.
- CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models34
The CustomNet is introduced, a novel object customization approach that explicitly incorporates 3D novel view synthesis capabilities into the object customization process, and facilitates zero-shot object customization without test-time optimization, offering simultaneous control over the viewpoints, location, and background.
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- CustomNet: Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models10
CustomNet is presented, a unified encoder-based object customization framework that explicitly incorporates 3D novel view synthesis capabilities into the customization process, and outperforms other customization methods regarding identity preservation, diversity, and harmony.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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