https://gitee.com/HarveyYeung/GLNet-TCYB2022-MindSpore.git
공식 코드Global-and-Local Collaborative Learning for Co-Salient Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Co-Salient Object Detection is a computational problem that aims at highlighting the common and salient foreground regions (or objects) in an image group. Please also refer to the online benchmark: http://dpfan.net/cosod3k/
<span style="color:grey; opacity: 0.6">( Image credit: Taking a Deeper Look at Co-Salient Object Detection, CVPR2020 )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Global-and-Local Collaborative Learning for Co-Salient Object Detection
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Group Collaborative Learning for Co-Salient Object Detection
Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detection
Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
Self-supervised co-salient object detection via feature correspondence at multiple scales
Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
Memory-aided Contrastive Consensus Learning for Co-salient Object Detection
Co-Salient Object Detection with Co-Representation Purification
Global-and-Local Collaborative Learning for Co-Salient Object Detection
Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
Advancing Referring Expression Segmentation Beyond Single Image
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.