https://github.com/xahidbuffon/SVAM-Net
공식 코드SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
Papers with Code 아카이브
Saliency Prediction
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A saliency map is a model that predicts eye fixations on a visual scene. Saliency prediction is informed by the human visual attention mechanism and predicts the possibility of the human eyes to stay in a certain position in the scene.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xahidbuffon/funie-gan
공식 코드Fast Underwater Image Enhancement for Improved Visual Perception
https://github.com/ysyscool/DINet
공식 코드https://github.com/yun-liu/DNA
공식 코드DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection
https://github.com/zengxianyu/mws
공식 코드https://github.com/zwbx/BTS-Net
공식 코드BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection
https://gitlab.com/abanitalebi/lbvs-3d
공식 코드A Learning-Based Visual Saliency Prediction Model for Stereoscopic 3D Video (LBVS-3D)
https://gitlab.com/abanitalebi/lbvs-hdr
공식 코드A Learning-Based Visual Saliency Fusion Model for High Dynamic Range Video (LBVS-HDR)
https://github.com/AhmetSencan/MaskSplit-Self-supervised-Meta-learning-for-Few-shot-Semantic-Segmentation
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation
https://github.com/Aline-Farias/DAVE
DAVE: A Deep Audio-Visual Embedding for Dynamic Saliency Prediction
https://github.com/Amrit-pal-Singh/Saliency-Detection
https://github.com/DengPingFan/S-measure
https://github.com/DengPingFan/SOC-DataAug
https://github.com/EPFL-VILAB/XDEnsembles
https://github.com/EkdeepSLubana/OrthoReg
Faster gaze prediction with dense networks and Fisher pruning
https://github.com/Hey1Li/Saliency-Relevance-Propagation
https://github.com/IRVLab/Deep-SESR
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
https://github.com/IRVLab/SUIM
Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
https://github.com/IRVLab/SUIM-Net
Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
https://github.com/IRVLab/funie-gan
Fast Underwater Image Enhancement for Improved Visual Perception
https://github.com/Linardos/SalEMA
Simple vs complex temporal recurrences for video saliency prediction
https://github.com/ShuhanChen/RAS_ECCV18
https://github.com/TingdiRen/URSCT-SESR
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
https://github.com/ZhaoJ9014/Multi-Human-Parsing
https://github.com/chenxy99/ANOC
Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model
https://github.com/come880412/STSANet
Spatio-Temporal Self-Attention Network for Video Saliency Prediction
https://github.com/gradio-app/saliency
Contextual Encoder-Decoder Network for Visual Saliency Prediction
https://github.com/horanyinora/gazeworkshop.github.io
TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking
https://github.com/hyf015/gaze_prediction
Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition
https://github.com/imatge-upc/egocentric-2016-saliency
https://github.com/imatge-upc/saliency-2018-videosalgan
https://github.com/imatge-upc/saliency-2019-SalBCE
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
https://github.com/imatge-upc/saliency-salgan-2017
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
https://github.com/islab-sophia/odisal
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling
https://github.com/lcc157/code
https://github.com/leafy-lee/E-commercial-dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.