https://github.com/imatge-upc/SalEMA
공식 코드Simple vs complex temporal recurrences for video saliency prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Saliency prediction aims to predict important locations in a visual scene. It is a per-pixel regression task with predicted values ranging from 0 to 1.
Benefiting from deep learning research and large-scale datasets, saliency prediction has achieved significant success in the past decade. However, it still remains challenging to predict saliency maps on images in new domains that lack sufficient data for data-hungry models.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Simple vs complex temporal recurrences for video saliency prediction
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
Shallow and Deep Convolutional Networks for Saliency Prediction
How Does Audio Influence Visual Attention in Omnidirectional Videos? Database and Model
RSKDD-Net: Random Sample-based Keypoint Detector and Descriptor
Data Augmentation via Latent Diffusion for Saliency Prediction
Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics
Mesh Mamba: A Unified State Space Model for Saliency Prediction in Non-Textured and Textured Meshes
TranSalNet: Towards perceptually relevant visual saliency prediction
Direction Concentration Learning: Enhancing Congruency in Machine Learning
Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model
A Deep Learning Framework for Visual Attention Prediction and Analysis of News Interfaces
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling
Correlation of Object Detection Performance with Visual Saliency and Depth Estimation
AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
ATSal: An Attention Based Architecture for Saliency Prediction in 360 Videos
PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
Hierarchical Domain-Adapted Feature Learning for Video Saliency Prediction
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency Prediction
End-to-End Saliency Mapping via Probability Distribution Prediction
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.