显著性目标检测代码全汇总！(包含2D、3D、4D以及Video)
显著性目标检测代码全汇总！(包含2D、3D、4D以及Video)
转载于极市开发者原创投稿https://mp.weixin.qq.com/s/ZSytEsVSjBU_zjy5YPxPeA
这里是加以翻译
SOD CNNs-based Read List
在这个知识库中，我们主要关注基于深度学习的显著性方法(2D RGB, 3D RGB-D, Video SOD and 4D Light Field) ，并提供总结(Code and Paper).。我们希望这份回购能帮助大家更好地理解深度学习时代的显著性检测。 评估指标。
❗ 2D SOD: Add five papesr ECCV20
❗ 3D SOD: Add nine papers ECCV20 and two ACMM20 papers
❗ Video SOD : Add three papers ECCV20, Continuously Updating!
???? We will keep updating it. ????
Content:
- An overview of the Paper List
- 2D RGB Saliency Detection
- 3D RGB Saliency Detection
- 4D Light Field Saliency Detection
- Video Saliency Detection
- Survery and earlier Methods
- The SOD dataset download
- Evaluation Metrics
Overall
2D RGB Saliency Detection
2020
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | AAAI | Progressive Feature Polishing Network for Salient Object Detection | Paper/Code |
| 02 | AAAI | Global Context-Aware Progressive Aggregation Network for Salient Object Detection | Paper/Code |
| 03 | AAAI | F3Net: Fusion, Feedback and Focus for Salient Object Detection | Paper/Code |
| 04 | AAAI | Multi-spectral Salient Object Detection by Adversarial Domain Adaptation | Paper/Code |
| 05 | AAAI | Multi-Type Self-Attention Guided Degraded Saliency Detection | Paper/Code |
| 06 | CVPR | Weakly-Supervised Salient Object Detection via Scribble Annotations | Paper/Code |
| 07 | CVPR | Taking a Deeper Look at the Co-salient Object Detection | Paper/Code |
| 08 | CVPR | Multi-scale Interactive Network for Salient Object Detection | Paper/Code |
| 09 | CVPR | Interactive Two-Stream Decoder for Accurate and Fast Saliency Detection | Paper/Code |
| 10 | CVPR | Label Decoupling Framework for Salient Object Detection | Paper/Code |
| 11 | CVPR | Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection | Paper/Code |
| ???? 12 | ECCV | Highly Efficient Salient Object Detection with 100K Parameters | Paper/Code |
| ???? 13 | ECCV | n-Reference Transfer Learning for Saliency Prediction | Paper/Code |
| ???? 14 | ECCV | Gradient-Induced Co-Saliency Detection | Paper/Code |
| ???? 13 | ECCV | Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection | Paper/Code |
| ???? 15 | ECCV | Suppress and Balance: A Simple Gated Network for Salient Object Detection | Paper/Code |
2019
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | AFNet: Attentive Feedback Network for Boundary-aware Salient Object Detection | Paper/Code |
| 02 | CVPR | BASNet: Boundary Aware Salient Object Detection | Paper/Code |
| 03 | CVPR | CPD: Cascaded Partial Decoder for Accurate and Fast Salient Object Detection | Paper/Code |
| 04 | CVPR | Multi-source weak supervision for saliency detection | Paper/Code |
| 05 | CVPR | MLMSNet:A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision | Paper/Code |
| 06 | CVPR | CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection | Paper/Code |
| 07 | CVPR | PoolNet: A Simple Pooling-Based Design for Real-Time Salient Object Detection | Paper/Code |
| 08 | CVPR | An Iterative and Cooperative Top-down and Bottom-up Inference Network for Salient Object Detection | Paper/Code |
| 09 | CVPR | Pyramid Feature Attention Network for Saliency detection | Paper/Code |
| 10 | AAAI | Deep Embedding Features for Salient Object Detection | Paper/Code |
| 11 | ICIP | Salient Object Detection Via Deep Hierarchical Context Aggregation And Multi-Layer Supervision | Paper/Code |
| 12 | IEEE TCSVT | AADF-Net: Aggregating Attentional Dilated Features for Salient Object | Paper/Code |
| 13 | IEEE TCyb | ROSA: Robust Salient Object Detection against Adversarial Attacks | Paper/Code |
| 14 | arXiv | DSAL-GAN: DENOISING BASED SALIENCY PREDICTION WITH GENERATIVE ADVERSARIAL NETWORKS | Paper/Code |
| 15 | arXiv | SAC-Net: Spatial Attenuation Context for Salient Object Detection | Paper/Code |
| 16 | arXiv | SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection | Paper/Code |
| 17 | arXiv | Region Refinement Network for Salient Object Detection | Paper/Code |
| 18 | arXiv | Contour Loss: Boundary-Aware Learning for Salient Object Segmentation | Paper/Code |
| 19 | arXiv | OGNet: Salient Object Detection with Output-guided Attention Module | Paper/Code |
| 20 | arXiv | Edge-guided Non-local Fully Convolutional Network for Salient Object Detection | Paper/Code |
| 21 | ICCV | FLoss:Optimizing the F-measure for Threshold-free Salient Object Detection | Paper/Code |
| 22 | ICCV | Stacked Cross Refinement Network for Salient Object Detection | Paper/Code |
| 23 | ICCV | Selectivity or Invariance: Boundary-aware Salient Object Detection | Paper/Code |
| 24 | ICCV | HRSOD:Towards High-Resolution Salient Object Detection | Paper/Code |
| 25 | ICCV | EGNet:Edge Guidance Network for Salient Object Detection | Paper/Code |
| 26 | ICCV | Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection | Paper/Code |
| 27 | ICCV | Employing Deep Part-Object Relationships for Salient Object Detection | Paper/Code |
| 28 | NeurIPS | Deep Robust Unsupervised Saliency Prediction With Self-Supervision | Paper/Code |
2018
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | A Bi-Directional Message Passing Model for Salient Object Detection | Paper/Code |
| 02 | CVPR | PiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection | Paper/Code |
| 03 | CVPR | PAGR: Progressive Attention Guided Recurrent Network for Salient Object Detection | Paper/Code |
| 04 | CVPR | Learning to promote saliency detectors | Paper/Code |
| 05 | CVPR | Detect Globally, Refine Locally: A Novel Approach to Saliency Detection | Paper/Code |
| 06 | CVPR | Salient Object Detection Driven by Fixation Prediction | Paper/Code |
| 07 | IJCAI | R3Net: Recurrent Residual Refinement Network for Saliency Detection | Paper/Code |
| 08 | IJCAI | LFR: Salient Object Detection by Lossless Feature Reflection | Paper/Code |
| 09 | ECCV | Contour Knowledge Transfer for Salient Object Detection | Paper/Code |
| 10 | ECCV | Reverse Attention for Salient Object Detection | Paper/Code |
| 11 | IEEE TIP | An unsupervised game-theoretic approach to saliency detection | Paper/Code |
| 12 | arXiv | Agile Amulet: Real-Time Salient Object Detection with Contextual Attention | Paper/Code |
| 13 | arXiv | HyperFusion-Net: Densely Reflective Fusion for Salient Object Detection | Paper/Code |
| 14 | arXiv | (TBOS)Three Birds One Stone: A Unified Framework for Salient Object Segmentation, Edge Detection and Skeleton Extraction | Paper/Code |
2017
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | DSS: Deeply Supervised Salient Object Detection with Short Connections | Paper/Code |
| 02 | CVPR | Non-Local Deep Features for Salient Object Detection | Paper/Code |
| 03 | CVPR | Learning to Detect Salient Objects with Image-level Supervision | Paper/Code |
| 04 | CVPR | SalGAN: visual saliency prediction with adversarial networks | Paper/Code |
| 05 | ICCV | A Stagewise Refinement Model for Detecting Salient Objects in Images | Paper/Code |
| 06 | ICCV | Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection | Paper/Code |
| 07 | ICCV | Learning Uncertain Convolutional Features for Accurate Saliency Detection | Paper/Code |
2016
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | DHSNet: Deep hierarchical saliency network for salient object detection | Paper/Code |
| 02 | CVPR | ELD: Deep Saliency with Encoded Low level Distance Map and High Level Features | Paper/Code |
| 03 | ECCV | RFCN: Saliency detection with recurrent fully convolutional networks | Paper/Code |
3D RGB-D Saliency Detection
2020
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | IEEE TIP | ICNet: Information Conversion Network for RGB-D Based Salient Object Detection | Paper/Code |
| 02 | CVPR | JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection | Paper/Code |
| 03 | CVPR | UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders | Paper/Code |
| 04 | CVPR | A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object Detection | Paper/Code |
| 05 | CVPR | Select, Supplement and Focus for RGB-D Saliency Detection | Paper/Code |
| 06 | CVPR | Learning Selective Self-Mutual Attention for RGB-D Saliency Detection | Paper/Code |
| ???? 07 | ECCV | Accurate RGB-D Salient Object Detection via Collaborative Learning | Paper/Code |
| ???? 08 | ECCV | Cross-Modal Weighting Network for RGB-D Salient Object Detection | Paper/Code |
| ???? 09 | ECCV | BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network | Paper/Code |
| ???? 10 | ECCV | Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection | Paper/Code |
| ???? 11 | ECCV | Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection | Paper/Code |
| ???? 12 | ECCV | RGB-D Salient Object Detection with Cross-Modality Modulation and Selection | Paper/Code |
| ???? 13 | ECCV | Cascade Graph Neural Networks for RGB-D Salient Object Detection | Paper/Code |
| ???? 14 | ECCV | A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection | Paper/Code |
| ???? 15 | ECCV | Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency Detection | Paper/Code |
| ???? 16 | ACMM | Is Depth Really Necessary for Salient Object Detection? | Paper/Code |
| ???? 17 | ACMM | A Top-down and Adaptive Fusion Network for RGB-D Salient Object Detection | Paper/Code |
2019
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | ICCV | DMRA: Depth-induced Multi-scale Recurrent Attention Network for Saliency Detection | Paper/Code |
| 02 | CVPR | CPFP: Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection | Paper/Code |
| 03 | IEEE TIP | Three-stream Attention-aware Network for RGB-D Salient Object Detection | Paper/Code |
| 04 | IEEE PR | Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection | Paper/Code |
| 05 | arXiv | AFNet: Adaptive Fusion for RGB-D Salient Object Detection | Paper/Code |
| 06 | IEEE TNNLS | D3Net:Rethinking RGB-D Salient Object Detection: Models, Datasets, and Large-Scale Benchmarks | Paper/Code |
| 07 | arXiv | CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse | Paper/Code |
2018
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | PCA: Progressively Complementarity-aware Fusion Network for RGB-D Salient Object Detection | Paper/Code |
| 02 | IEEE TIP | Co-saliency detection for RGBD images based on multi-constraint feature matching and cross label propagation | Paper/Code |
| 03 | ICME | PDNet: Prior-Model Guided Depth-enhanced Network for Salient Object Detection | Paper/Code |
2017
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | ICCV | Learning RGB-D Salient Object Detection using background enclosure, depth contrast, and top-down features | Paper/Code |
| 02 | IEEE TIP | DF: RGBD Salient Object Detection via Deep Fusion | Paper/Code |
| 03 | IEEE TCyb | CTMF: Cnns-based rgb-d saliency detection via cross-view transfer and multiview fusion | Paper/Code |
Traditional methods
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | MTA | RGBD co-saliency detection via multiple kernel boosting and fusion | Paper/Code |
| 02 | ICCV17 | An Innovative Salient Object Detection Using Center-Dark Channel Prior | Paper/Code |
| 03 | IEEE SPL | Saliency detection for stereoscopic images based on depth confidence analysis and multiple cues fusion | Paper/Code |
| 04 | IEEE SPL | RGBD Co-saliency Detection via Bagging-Based Clustering | Paper/Code |
| 05 | CVPR | Exploiting Global Priors for RGB-D Saliency Detection | Paper/Code |
4D Light Field Saliency Detection
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | TOMM | MCA: Saliency Detection on Light Field: A Multi-Cue Approach | Paper/Code |
| 02 | IJCAI | DILF: Saliency Detection with a Deeper Investigation of Light Field | Paper/Code |
| 03 | CVPR | WSC: A Weighted Sparse Coding Framework for Saliency Detection | Paper/Code |
| 04 | IEEE PAMI | Saliency Detection on Light-Field | Paper/Code |
| 05 | ICCV | Deep Learning for Light Field Saliency Detection | Paper/Code |
| 06 | NeurIPS | Memory-oriented Decoder for Light Field Salient Object Detection | Paper/Code |
| 07 | AAAI | Exploit and Replace: An Asymmetrical Two-Stream Architecture for Versatile Light Field Saliency Detection | Paper/Code |
Video Salient Object Detection
2020
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | CVPR | STAViS: Spatio-Temporal AudioVisual Saliency Network | Paper/Code |
| ???? 02 | ECCV | Unified Image and Video Saliency Modeling | Paper/Code |
| ???? 03 | ECCV | Measuring the importance of temporal features in video saliency | Paper/Code |
| ???? 04 | ECCV | TENet: Triple Excitation Network for Video Salient Object Detection | Paper/Code |
2019
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | ICCV | Motion Guided Attention for Video Salient Object Detection | Paper/Code |
| 02 | ICCV | Semi-Supervised Video Salient Object Detection Using Pseudo-Labels | Paper/Code |
| 03 | ICCV | Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection | Paper/Code |
| 04 | ICCV | RANet：Ranking attention Network for Fast Video Object Segmentation | Paper/Code |
| 05 | CVPR | Shifting More Attention to Video Salient Objection Detection | Paper/Code |
| 06 | CVPR | Learning Unsupervised Video Object Segmentation through Visual Attention | Paper/Code |
| 07 | CVPR | See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks | Paper/Code |
2018
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | ECCV | Pyramid Dilated Deeper CoonvLSTM for Video Salient Object Detection | Paper/Code |
| 02 | ECCV | DeepVS: A Deep Learning Based Video Saliency Prediction Approach | Paper/Code |
| 03 | CVPR | Revisiting Video Saliency: A Large-scale Benchmark and a New Model | Paper/Code |
| 04 | CVPR | Flow Guided Recurrent Neural Encoder for Video Salient Object Detection | Paper/Code |
| 05 | IEEE TIP | Video Salient Object Detection via Fully Convolutional Networks | Paper/Code |
2017
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | IEEE TIP | Learning to Detect Video Saliency with HEVC Features | Paper/Code |
Earlier Methods
| No. | Pub. | Title | Links |
|---|---|---|---|
| 01 | IEEE TIP15 | Salient object detection: A benchmark | Paper/Code |
| 02 | IEEE TCSVT18 | Review of visual saliency detectionwith comprehensive information | Paper/Code |
| 03 | ACM TIST18 | A review of co-saliency detection algorithms: Fundamentals, applications, and challenges | Paper/Code |
| 04 | IEEE TSP18 | Advanced deep-learning techniques for salient and category-specific object detection: A survey | Paper/Code |
| 05 | IJCV18 | Attentive systems: A survey | Paper/Project |
| 06 | ECCV18 | Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground | Paper/Code |
| 07 | CVM18 | Salient object detection: A survey | Paper/Code |
| 08 | IEEE TNNLS19 | Salient Object detection with deep learning: Areview | Paper/Code |
| 09 | arXiv19 | Salient Object Detection in the Deep Learning Era-An In-Depth Survey | Paper/Code |
| 10 | GitHub20 | RGB-D Salient Object Detection: A Survey | Paper/Code |
The part of the collection is thanks to Deng-Ping Fan and Tao Zhou.
- Salient Object Detection in the Deep Learning Era: An In-Depth Survey. paper link.
- This is a paper list published by another author. here
- RGB-D Salient Object Detection: A Survey. project link.
与最先进的比较
显著性目标检测数据集下载
- 2D SOD datasets download1 or download2, download3.
- 3D SOD datasets download.
- 4D SOD datasets download.
- Video SOD datasets download.
Evaluation Metrics【评价指标】
-
Saliency maps evaluation.【特征图评价】
该链接几乎包括用于显著对象检测的所有评估指标，包括E-Measure、S-Measure、F-Measure、MAE Score和PR曲线或BAR指标。 你可以在这里找到 【链接】. -
Saliency Dataset evaluation.【显著性数据集评估】
该方法可以在二进制显著性数据集上计算Obj.Area和Obj.Contrast的比值。此工具箱包含两个评估指标，包括obj(Object).Area和obj.Contrast。
你可以在这里找到【链接】.