UIE
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Underwater image enhancement is a technique used to improve the quality of underwater images. Due to the unique properties of the underwater environment, images captured underwater often suffer from degradation caused by absorption and scattering of light. These effects can result in low contrast, blurred images with a dominant blue or green color cast. Enhancement techniques aim to correct these issues and improve the visibility within the image. These methods can include color correction to remove the color cast, contrast enhancement to improve the visibility of underwater objects, and dehazing techniques to reduce the scattering effect. These enhancements are crucial in various applications, including underwater exploration, marine biology research, underwater archaeology, and in improving the performance of underwater vision systems used in autonomous underwater vehicles.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/LintaoPeng/SS-UIE
공식 코드Adaptive Dual-domain Learning for Underwater Image Enhancement
https://github.com/LintaoPeng/U-shape_Transformer
공식 코드https://github.com/Lu-Yang666/LDNet
공식 코드Label Drop for Multi-Aspect Relation Modeling in Universal Information Extraction
https://github.com/OUCVisionGroup/CLIP-UIE
공식 코드Underwater Image Enhancement by Diffusion Model with Customized CLIP-Classifier
https://github.com/PREDICT-EPFL/polydome
공식 코드Data-driven input reconstruction and experimental validation
https://github.com/RQ-Wu/UnderwaterRanker
공식 코드Underwater Ranker: Learn Which Is Better and How to Be Better
https://github.com/TingdiRen/URSCT-SESR
공식 코드Reinforced Swin-Convs Transformer for Underwater Image Enhancement
https://github.com/alexande-rchan/fdce-net
공식 코드FDCE-Net: Underwater Image Enhancement with Embedding Frequency and Dual Color Encoder
https://github.com/bachzz/uw-diffphys
공식 코드Underwater Image Enhancement with Physical-based Denoising Diffusion Implicit Models
https://github.com/chenydong/o-mamba
공식 코드O-Mamba: O-shape State-Space Model for Underwater Image Enhancement
https://github.com/chenydong/pa-diff
공식 코드Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image Enhancement
https://github.com/chocowu/lasuie
공식 코드https://github.com/dasepli/codeie
공식 코드CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors
https://github.com/ddz16/UIEDP
공식 코드https://github.com/ddz16/UWEnhancer
공식 코드A Physical Model-Guided Framework for Underwater Image Enhancement and Depth Estimation
https://github.com/fansuregrin/raune-net
공식 코드RAUNE-Net: A Residual and Attention-Driven Underwater Image Enhancement Method
https://github.com/gargi884/sinet-uie
공식 코드SINET: Sparsity-driven Interpretable Neural Network for Underwater Image Enhancement
https://github.com/gewu-lab/crab
공식 코드Crab: A Unified Audio-Visual Scene Understanding Model with Explicit Cooperation
https://github.com/ixiaohuihuihui/gcc-net
공식 코드A Gated Cross-domain Collaborative Network for Underwater Object Detection
https://github.com/kkoucy/rd-uie
공식 코드RD-UIE: Relation-Driven State Space Modeling for Underwater Image Enhancement
https://github.com/lewis081/ccl-net
공식 코드Underwater Image Enhancement with Cascaded Contrastive Learning
https://github.com/ostars/ruie
공식 코드RUIE: Retrieval-based Unified Information Extraction using Large Language Model
https://github.com/pengts/fsuie
공식 코드FSUIE: A Novel Fuzzy Span Mechanism for Universal Information Extraction
https://github.com/rockwenjj/syreanet
공식 코드https://github.com/underwater-lab-shu/uierl
공식 코드UIERL: Internal-External Representation Learning Network for Underwater Image Enhancement
https://github.com/vidya-rejul/uie-snn
공식 코드Underwater Image Enhancement by Convolutional Spiking Neural Networks
https://github.com/weitunglin/pixmamba
공식 코드https://github.com/wenge-research/YAYI-UIE
공식 코드YAYI-UIE: A Chat-Enhanced Instruction Tuning Framework for Universal Information Extraction
https://github.com/windysprint/uvz
공식 코드Underwater Variable Zoom: Depth-Guided Perception Network for Underwater Image Enhancement
https://github.com/yzbouc/uveb
공식 코드UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement
https://github.com/zhenqifu/Twice-Mixing
공식 코드Twice Mixing: A Rank Learning based Quality Assessment Approach for Underwater Image Enhancement
https://github.com/zhenqifu/puie-net
공식 코드https://github.com/zhihefang/SFGNet
공식 코드Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement
https://github.com/zhihefang/wf-diff
공식 코드https://github.com/zjunlp/adakgc
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.