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- 2,959
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- Towards Real-World Blind Face Restoration with Generative Facial Prior676
This work proposes GFP-GAN that leverages rich and diverse priors encapsulated in a pretrained face GAN for blind face restoration that achieves superior performance to prior art on both synthetic and real-world datasets.
- Effective Whole-body Pose Estimation with Two-stages Distillation446
This work presents a two-stage pose Distillation for Whole-body Pose estimators, named DWPose, to improve their effectiveness and efficiency and releases a series of models with different sizes, from tiny to large, for satisfying various downstream tasks.
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- Instances as Queries362
For the first time, it is demonstrated that a simple end-to-end query based framework can achieve the state-of-the-art performance in various instance-level recognition tasks.
- Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset342
This paper proposes a novel end-to-end attention-guided method based on multi-branch convolutional neural network that can produce high fidelity enhancement results for low-light images and outperforms the current state-of-the-art methods both quantitatively and visually.
- Human Pacman: a mobile, wide-area entertainment system based on physical, social, and ubiquitous computing335
Human Pacman research is a physical role-playing augmented-reality computer fantasy together with real human–social and mobile gaming that emphasizes collaboration and competition between players in a wide outdoor physical area which allows natural wide-area human–physical movements.
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- One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer186
This work designs a one-stage pipeline for expressive whole-body mesh recovery, named OSX, without separate networks for each part, and designs a Component Aware Transformer (CAT) composed of a global body encoder and a local face/hand decoder.
- Seam-Driven Image Stitching182
This work proposes a seam-driven image stitching strategy where instead of estimating a geometric transform based on the best fit of feature correspondences, the goodness of a transform is evaluated based upon the resulting visual quality of the seam-cut.
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- Haze visibility enhancement: A Survey and quantitative benchmarking170
This paper provides a comprehensive survey of methods dealing with visibility enhancement of images taken in hazy or foggy scenes and provides a benchmark of a number of well known single-image methods, based on a recent dataset provided by Fattal and a newly generated scattering media dataset that contains ground truth images for quantitative evaluation.
- From Knowledge Distillation to Self-Knowledge Distillation: A Unified Approach with Normalized Loss and Customized Soft Labels166
This work unifies the formulations of the two tasks by decomposing and reorganizing the generic KD loss into a Normalized KD (NKD) loss and customized soft labels for both target class (image’s category) and non-target classes named Universal Self-KD (USKD).
- A minutely solar irradiance forecasting method based on real-time sky image-irradiance mapping model153
- A Contrast Enhancement Framework with JPEG Artifacts Suppression137
This work proposes a framework that suppresses compression artifacts as an integral part of the contrast enhancement procedure and shows that this approach can produce compelling results superior to those obtained by existing JPEG artifacts removal methods for several types of contrast enhancement problems.
- Towards Vivid and Diverse Image Colorization with Generative Color Prior135
This work aims at recovering vivid colors by leveraging the rich and diverse color priors encapsulated in a pretrained Generative Adversarial Networks (GAN) via a GAN encoder and incorporating these features into the colorization process with feature modulations.
- Unsupervised Learning for Intrinsic Image Decomposition From a Single Image134
This paper proposes a novel unsupervised intrinsic image decomposition framework, which relies on neither labeled training data nor hand-crafted priors, and directly learns the latent feature of reflectance and shading from unsuper supervised and uncorrelated data.
- Fast Video Object Segmentation Using the Global Context Module131
A real-time, high-quality semi-supervised video object segmentation algorithm that effectively summarizes and propagates information through the entire video, and uses constant memory regardless of the video length and costs substantially less memory and computation.
- Crossover Learning for Fast Online Video Instance Segmentation129
A novel crossover learning scheme that uses the instance feature in the current frame to pixel-wisely localize the same instance in other frames to enable efficient cross-frame instance-to-pixel relation learning and brings cost-free improvement during inference.
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- Fast Guided Global Interpolation for Depth and Motion102
This work proposes a unified approach that casts the fundamental guided interpolation problem into a hierarchical, global optimization framework, and achieves quantitatively competitive results on various benchmark evaluations, while running much faster than other competing methods designed specifically for either depth upsampling or motion interpolation.
- Detail Preserving Depth Estimation from a Single Image Using Attention Guided Networks99
This work proposes a network consisting of a Dense Feature Extractor (DFE) and a Depth Map Generator (DMG) that can predict depth map in about 15 fps and can preserve better structural details of the scene depth.
- An evaluation of wearable activity monitoring devices95
An evaluation on the most popular devices available on the market (in particular Fitbit and Nike+) is performed and the findings are reported in terms of accuracy, type of data provided, available APIs, and user experience.
- Human Pacman: A Mobile Entertainment System with Ubiquitous Computing and Tangible Interaction over a Wide Outdoor Area93
Human Pacman is an interactive role-playing game that envisions to bring the computer gaming experience to a new level of emotional and sensory gratification by setting the real world as a playground.
- Temporally Efficient Vision Transformer for Video Instance Segmentation89
The proposed Temporally Efficient Vision Transformer (TeViT) is nearly convolution-free, which contains a transformer backbone and a query-based video instance segmentation head, which fully utilizes both frame-level and instance-level temporal context information and obtains strong temporal modeling capacity with negligible extra computational cost.
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- $$\mathrm {CT^2}$$: Colorization Transformer via Color Tokens78
This paper proposes an end-to-end transformer-based model to overcome the challenges of automatic image colorization and introduces color tokens into the approach and treats the colorization task as a classification problem, which increases the saturation of results.
- Magic Story Cube68
This research explores a new interface for children education and entertainment using physical cube to provide the user with multi-sensory experiences in the process of storytelling.
- Learning From Synthetic Photorealistic Raindrop for Single Image Raindrop Removal67
This work proposes the first photo-realistic dataset of synthetic adherent raindrops for training and introduces a detection network which has the awareness of the raindrop refraction as well as its blurring and the removal network that can well recover the image structure.
- Evidence for pre‐symptomatic transmission of coronavirus disease 2019 (COVID‐19) in China64
Between mid‐January and early February, provinces of mainland China outside the epicentre in Hubei province were on high alert for importations and transmission of COVID‐19.
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- The RST invariant digital image watermarking using Radon transforms and complex moments62
An approach of rotation, scaling, and translation (RST) invariant analysis for images achieves a set of completely invariant descriptors from the complex moments of the original image's Radon projection, and proposes a watermarking scheme which can resist global geometric transforms.
- Control Color: Multimodal Diffusion-Based Interactive Image Colorization58
Control Color is introduced, a multi-modal colorization method that leverages the pre-trained Stable Diffusion model, offering promising capabilities in highly controllable interactive image colorization and addressing the long-standing issues of color overflow and inaccurate coloring.
- Make Encoder Great Again in 3D GAN Inversion through Geometry and Occlusion-Aware Encoding58
This work introduces a novel encoder-based inversion framework based on EG3D, one of the most widely-used 3D GAN models, and uses the inherent properties of EG3D’s latent space to design a discriminator and a background depth regularization.
- Combined invariants to blur and rotation using Zernike moment descriptors55
This paper addresses a method for recognizing objects in an image in a way that is invariant to images’ blur and rotation transformations to improve the robustness to noises and outperforms other similar ones in the presence of various blur-degraded and rotation-transformed images.
- Active Learning for Open-set Annotation53
A new active learning framework called LfOSA is proposed, which boosts the classification performance with an effective sampling strategy to precisely detect examples from known classes for annotation and can achieve higher classification accuracy with lower annotation cost than state-of-the-art active learning methods.
- Fast Vehicle and Pedestrian Detection Using Improved Mask R-CNN52
A Resnet-86 network is adopted as a backbone that differs from the backbone structure of Res Net-101 in the Mask R-CNN algorithm within practical conditions to reduce the operation time and greatly improve accuracy.
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- AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference51
This paper presents AppealNet, a novel edge/cloud collaborative architecture that runs deep learning tasks more efficiently than state-of-the-art solutions by employing a two-head neural network architecture that explicitly takes inference difficulty into consideration and optimizes the tradeoff between accuracy and computation/communication cost of the edge/ cloud collaborative architecture.
- ViTKD: Practical Guidelines for ViT feature knowledge distillation50
This paper designs a series of controlled experiments and derives three practical guidelines for ViT's feature distillation and proposes the feature-based method ViTKD which brings consistent and considerable improvement to the student.
- Using Vehicle Synthesis Generative Adversarial Networks to Improve Vehicle Detection in Remote Sensing Images50
A learning method named Vehicle Synthesis Generative Adversarial Networks (VS-GANs) to generate annotated vehicles from remote sensing images that significantly improves the generalization capability of vehicle detectors.
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- Lung nodules detection using grey wolf optimization by weighted filters and classification using CNN46
A well-performing method to detect and classify lung cancer among three classes using the Grey Wolf Optimization algorithm with a weighted filter to reduce noise in images, followed by segmentation using watershed transformation and dilation operations.
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- L-CoDer: Language-Based Colorization with Color-Object Decoupling Transformer40
This work introduces transformer into language-based colorization to tackle the aforementioned issues while keeping the language decoupling property, and unifies the modalities of image and language, and further performs color conditions evolving with image features in a coarse-to-fine manner.
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- NTIRE 2021 Challenge on Video Super-Resolution36
This paper presents evaluation results from two competition tracks as well as the proposed solutions to the NTIRE 2021 Challenge on Video Super-Resolution, and develops conventional video SR methods focusing on the restoration quality.
- Dual Semantic Fusion Network for Video Object Detection35
This work proposes a dual semantic fusion network (abbreviated as DSFNet) to fully exploit both frame-level and instance-level semantics in a unified fusion framework without external guidance and introduces a geometric similarity measure into the fusion process to alleviate the influence of information distortion caused by noise.
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- Prophet model and Gaussian process regression based user traffic prediction in wireless networks34
Experimental results demonstrate that the proposed model outperforms the existing time series prediction method.
- An improved spatial temporal graph convolutional network for robust skeleton-based action recognition33
The comprehensive experiments demonstrate that the proposed IST-GCN model possesses outstanding performance in terms of both accuracy and robustness when skeleton samples are incomplete and noisy compared with the state-of-the-art (SOTA) approach.
- Natural Language Processing Combined with ICD-9-CM Codes as a Novel Method to Study the Epidemiology of Allergic Drug Reactions32
Using NLP with ICD-9-CM codes improved identification of allergic drug reactions and resulted in a decrease in manual chart review effort, which will facilitate large epidemiology studies of this understudied area.
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- Human–large language model collaboration in clinical medicine: a systematic review and meta-analysis28
- Composite Photograph Harmonization with Complete Background Cues28
This work investigates the usage of a target background and finds that a complete background plays a vital role in both seamlessly blending and harmonization and develops a network to learn the composition process given an imperfect alpha matte with appearance features extracted from the complete background to adjust color distribution.
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- Do We Really Need Temporal Convolutions in Action Segmentation?24
This paper presents a pure Transformer-based model without temporal convolutions in action segmentation, called Temporal U-Transformer, and proposes a boundary-aware loss based on the distribution of similarity scores between frames from attention modules to improve the ability to recognize boundaries.
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- Rethinking Knowledge Distillation via Cross-Entropy21
This work decomposes the KD loss to explore its relation with the original cross-entropy (CE) loss, and proposes a new KD loss (NKD), which achieves state-of-the-art performance on CIFAR-100 and ImageNet.
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- Hybrid Warping Fusion for Video Frame Interpolation8
This work explicitly investigates the warping step and proposes a way to combine the strength from using both forward and backward warping, and introduces hybrid warping fusion for frame interpolation.
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- A Diffusion-Based Framework for Occluded Object Movement7
This work proposes a Diffusion-based framework specifically designed for Occluded Object Movement, named DiffOOM, which consists of two parallel branches that perform object de-occlusion and movement simultaneously.
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- PerTouch: VLM-Driven Agent for Personalized and Semantic Image Retouching6
This work proposes a unified diffusion-based image retouching framework called PerTouch, and develops a VLM-driven agent to handle both strong and weak user instructions, which supports semantic-level image retouching while maintaining global aesthetics.
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- Multi-scale perceptual image super-resolution reconstruction based on coordinate attention mechanism–
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- Practice of Japanese Publicity Translation of Chinese Ceramics from the Perspective of Skopos Theory–
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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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