https://github.com/vlad-winter/NLP20-FakePapers
Visual Saliency Detection Based on Multiscale Deep CNN Features
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Saliency Detection is a preprocessing step in computer vision which aims at finding salient objects in an image.
Source: An Unsupervised Game-Theoretic Approach to Saliency Detection
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Visual Saliency Detection Based on Multiscale Deep CNN Features
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
Contextual Encoder-Decoder Network for Visual Saliency Prediction
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.