Papers with Code 아카이브
Saliency Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 4
- 보존된 평가 기록
- 13
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/lhaof/fast-salient-object-detection
https://github.com/luoyan407/n-reference
https://github.com/nvinden/7ChannelEML
Contextual Encoder-Decoder Network for Visual Saliency Prediction
https://github.com/open-mmlab/mmpose
https://github.com/remega/LEDOV-eye-tracking-database
Predicting Video Saliency with Object-to-Motion CNN and Two-layer Convolutional LSTM
https://github.com/rowantseng/FUnIE-GAN-PyTorch
Fast Underwater Image Enhancement for Improved Visual Perception
https://github.com/the-super-toys/glimpse-models
Faster gaze prediction with dense networks and Fisher pruning
https://github.com/wangxiao5791509/cmSalGAN_PyTorch
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
https://github.com/wenguanwang/deepattention
https://github.com/xahidbuffon/Deep_SESR
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
https://github.com/xahidbuffon/SUIM
Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
https://github.com/yahsieh37/Visual-Saliency-Prediction
Contextual Encoder-Decoder Network for Visual Saliency Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.