Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileWorks54 from public data
- Multi-Scale Progressive Fusion Network for Single Image Deraining859
This work explores the multi-scale collaborative representation for rain streaks from the perspective of input image scales and hierarchical deep features in a unified framework, termed multi- scale progressive fusion network (MSPFN) for single image rain streak removal.
- 544
- 473
- 332
- Hierarchical dense recursive network for image super-resolution242
A novel hierarchical dense connection network (HDN) is advocated for image SR that outperforms the state-of-the-art methods in terms of quantitative indicators and realistic visual effects, as well as enjoys a fast and accurate reconstruction.
- 190
- 173
- Deep Distillation Recursive Network for Remote Sensing Imagery Super-Resolution144
Experiments on Kaggle Open Source Dataset and Jilin-1 video satellite images illustrate that DDRN outperforms the conventional CNN-based baselines and some state-of-the-art feature extraction approaches.
- 131
- 129
- 115
- 107
- Omniscient Video Super-Resolution92
This paper proposes an omniscient framework to not only utilize the preceding SR output, but also leverage the SR outputs from the present and future to enable a generator to behave better than its counterparts under other frameworks.
- Ultra-dense GAN for satellite imagery super-resolution89
An ultra-dense GAN (udGAN) is proposed for image SR, where the internal layout of the residual block is reformed into a two-dimensional matrix topology, which can provide additional diagonal connections so that the model can still accomplish enough pathways with fewer layers.
- 72
- Degrade Is Upgrade: Learning Degradation for Low-Light Image Enhancement68
A novel two-step generation network for degradation learning and content refinement, which is not only superior to one-step methods, but also capable of synthesizing sufficient paired samples to benefit the model training.
- 64
- 45
- 42
- Skywork UniPic 2.0: Building Kontext Model with Online RL for Unified Multimodal Model37
This work presents UniPic2-SD3.5M-Kontext, a 2B-parameter DiT model based on SD3.5-Medium, which achieves state-of-the-art image generation and editing while extending seamlessly into a unified multimodal framework, and proposes a novel Progressive Dual-Task Reinforcement strategy (PDTR), which effectively strengthens both tasks in a staged manner.
- 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.
- 36
- 32
- 23
- 19
- 18
- 18
- 13
- MRI-Based Radiomics and Delta-Radiomics Models of the Patella Predict the Radiographic Progression of Osteoarthritis: Data From the FNIH OA Biomarkers Consortium9
The MRI-based radiomics models of the patella all showed good predictive performance performed better than the clinical and biomarker models in predicting the radiographic progression of OA.
- Efficient lightweight network for video super-resolution8
A lightweight network for video super-resolution, namely Efficient Lightweight Network for Video Super-Resolution (ELNVSR), is proposed, which designs a Multi-group Block extracting long-distance spatial information to construct a lightweight Bidirection Alignment Module which is implicitly capable of fusing and propagating spatial-temporal information in a bidirectional way.
- Learning controlled and targeted communication with the centralized critic for the multi-agent system8
Experimental results demonstrated that partial agents with important information choose to send messages and targeted aggregate received information by identifying the relevant important information, which can still have better cooperation performance while reducing the communication traffic of the system.
- 8
- GEMINUS: Dual-aware Global and Scene-Adaptive Mixture-of-Experts for End-to-End Autonomous Driving7
GEMINUS, a Mixture-of-Experts end-to-end autonomous driving framework featuring a Global Expert and a Scene-Adaptive Experts Group, equipped with a Dual-aware Router achieves both adaptability and robustness across diverse scenarios.
- 5
- 4
- Omniscient Video Super-Resolution with Explicit-Implicit Alignment3
This work proposes an omniscient framework to fully explore the temporal relationships in the video, which encompasses both LR frames and SR outputs from the past, present, and future and integrates the explicit and implicit methods into an explicit-implicit alignment module to better utilize motion information.
- 3
- 3
- Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary2
A compressed adaptive image-sensing method based on an overcomplete ridgelet dictionary that can accurately identify smooth image blocks and more reasonably allocate sampling rates to obtain a reconstructed image with better quality.
- 2
- 1
- Lightweight Infrared and Visible Image Fusion Based on Nested Connections and Res2Net1
A novel method for infrared and visible image fusion, utilizing nested connections and frequency-domain decomposition techniques to effectively solve the problem of lost image detail features is introduced, by incorporating depthwise separable convolution technology.
- 1
- 1
- 1
- Improved scaling of spectrum decision mechanism in cognitive radio networks1
Through researched the mechanism of scaling judgment in psychology, a new and improved scale method were proposed, and the new scale method applied to spectrum decisions of cognitive radio networks, so that the measure of subjective judgment factors are more scientific and makes more explicit determination in spectrum decisions.
- 1
- P‐6.1: Demura Taking the Gamma Inconstancy into Account–
The relationship between luminance space and gray space is learned and the demura method taking gamma inconstancy into account is proposed, taking gamma inconstancy into account.
- –
- –
- –
- –
- Research on the Strategies of Wireless Network Based GIS Self-adaptation Transfer–
The method of transferring the interspaced data and information in new wireless environment based on the GIS self-adaptation transfer strategy, and analyzes self- Adaptation transfer characters, optimization principle which preserves the desired spatial update efficiency has been designed.
- Research on wireless network based GIS self-adaptation transfer model–
Wireless environment based GIS self-adaptation transfer model is introduced, self- Adaptation transfer characters are analyzed, and optimization principle for it is designed which preserves the desired spatial update efficiency.
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 2026-10-14. 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.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.