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Claim this profileWorks263 from public data
- Uformer: A General U-Shaped Transformer for Image Restoration2,405
Uformer, an effective and efficient Transformer-based architecture for image restoration, in which a hierarchical encoder-decoder network is built using the Transformer block and a learnable multi-scale restoration modulator in the form of a multi- scale spatial bias to adjust features in multiple layers of the Uformer decoder is proposed.
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- Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images489
The proposed Neighbor2Neighbor framework is able to enjoy the progress of state-of-the-art supervised denoising networks in network architecture design and avoids heavy dependence on the assumption of the noise distribution.
- Gabor Convolutional Networks420
A new deep model is proposed, termed Gabor Convolutional Networks (GCNs or Gabor CNNs), which incorporates Gabor filters into DCNNs to enhance the resistance of deep learned features to the orientation and scale changes.
- Prompt Distribution Learning367
This work presents prompt distribution learning for effectively adapting a pre-trained vision-language model to address downstream recognition tasks and employs a Gaussian distribution to model them effectively and derive a surrogate loss for efficient training.
- VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction349
This work proposes a progressive partitioning strategy to divide a large scene into multiple cells, where the training cameras and point cloud are properly distributed with an airspace-aware visibility criterion, and introduces decoupled appearance modeling into the optimization process to reduce appearance variations in the rendered images.
- Diffusion Model-Based Image Editing: A Survey328
This survey provides an exhaustive overview of existing methods using diffusion models for image editing, covering both theoretical and practical aspects in the field, and explores both earlier traditional context-driven and current multimodal conditional methods.
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- Domain General Face Forgery Detection by Learning to Weight179
This paper argues that different faces contribute differently to a detection model trained on multiple domains, making the model likely to fit domain-specific biases, and proposes the LTW approach based on the meta-weight learning algorithm, which configures different weights for face images from different domains.
- Multiple Instance Active Learning for Object Detection170
MI-AOD defines an instance uncertainty learning module, which leverages the discrepancy of two adversarial instance classifiers trained on the labeled set to predict instance uncertainty of the unlabeled set, and estimates the image uncertainty by re-weighting instances in a multiple instance learning (MIL) fashion.
- WaveDM: Wavelet-Based Diffusion Models for Image Restoration160
Evaluations on twelve benchmark datasets demonstrate that WaveDM achieves state-of-the-art performance with the efficiency that is comparable to traditional one-pass methods and over 100× faster than existing image restoration methods using vanilla diffusion models.
- Wavelet-Based Dual-Branch Network for Image Demoiréing158
Although designed for image demoireing, WDNet has been applied to two other low-levelvision tasks, outperforming state-of-the-art image deraining and derain-drop methods on the Rain100h and Raindrop800 data sets, respectively.
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- SketchyCOCO: Image Generation From Freehand Scene Sketches148
This work introduces the first method for automatic image generation from scene-level freehand sketches that allows for controllable image generation by specifying the synthesis goal via free hand sketches and builds a large-scale composite dataset called SketchyCOCO to support and evaluate the solution.
- Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression142
KSE is capable of simultaneously compressing each layer in an efficient way, which is significantly faster compared to previous data-driven feature map pruning methods, and significantly outperforms state-of-the-art methods.
- A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries142
A more comprehensive comparison of twenty-six 3D shape retrieval methods is performed by evaluating them on the common benchmark, compiled to be a superset of existing benchmarks and presents a new challenge to retrieval methods.
- A spatial-temporal approach for video caption detection and recognition141
A video caption detection and recognition system based on a fuzzy-clustering neural network (FCNN) classifier that improves the Chinese video-caption recognition accuracy from 13% to 86% on a set of news video captions.
- Pairwise constraint propagation by semidefinite programming for semi-supervised classification137
The general problem of learning from both pairwise constraints and unlabeled data is considered and it is proposed to learn a mapping that is smooth over the data graph and maps the data onto a unit hypersphere, where two must-link objects are mapped to the same point while two cannot- link objects are maps to be orthogonal.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; 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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