awesome-visual-relationship-detection
A curated list of visual relationship detection and related area resources
https://github.com/alisure-ml/awesome-visual-relationship-detection
Last synced: 6 days ago
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Visual Relationship Detection
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Dataset
- The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale - Alina Kuznetsova et al, IJCV 2018.
- Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations - Ranjay Krishna et al, [official web] (https://visualgenome.org/).
- Visual Relationship Detection with Language Priors - Lu et al, ECCV 2016 Oral.
- Video Visual Relation Dataset - Xindi Shang et al, 2018 ACM Multimedia Conference, [VidVRD-helper](https://github.com/xdshang/VidVRD-helper).
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Scene Graph
- Neural Motifs: Scene Graph Parsing with Global Context - Rowan Zellers et al, CVPR 2018, [[official pytorch=0.3.0 code]](https://github.com/rowanz/neural-motifs).
- Representation Learning for Scene Graph Completion via Jointly Structural and Visual Embedding - Hai Wan et al, IJCAI-18.
- Scene Graph Generation From Objects, Phrases and Region Captions - Yikang Li et al, ICCV 2017.
- Scene Graph Generation by Iterative Message Passing - Danfei Xu et al, CVPR 2017.
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Video Visual Relation Detection
- Video Visual Relation Detection - Xindi Shang et al, 2017 ACM Multimedia Conference, [Video Visual Relation Detection](http://software.nju.edu.cn/rentw/publication/mm17-shangxd_pot.pdf)
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Visual Relationship Detection
- Attentive Relational Networks for Mapping Images to Scene Graphs
- Large-Scale Visual Relationship Understanding - Ji Zhang et al, AAAI 2019.
- Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions - Stephan Baier et al.
- Visual Relationship Detection with Deep Structural Ranking - Kongming Liang et al, AAAI 2018, [[official pytorch=0.2.0 code]](https://github.com/GriffinLiang/vrd-dsr).
- Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information - Hsuan-Kung Yang et al, ECCV 2018 workshop.
- Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features - Xu Yang et al, ECCV 2018, [[tensorflow]](https://github.com/yangxuntu/vrd)
- Relation Networks for Object Detection - Han Hu et al, CVPR 2018 oral paper, [[official MXNet code]](https://github.com/msracver/Relation-Networks-for-Object-Detection), [[pytorch]](https://github.com/heefe92/Relation_Networks-pytorch).
- Tensorize, Factorize and Regularize: Robust Visual Relationship Learning - Seong Jae Hwang et al, CVPR 2018.
- Natural Language Guided Visual Relationship Detection - Wentong Liao et al.
- Context-Dependent Diffusion Network for Visual Relationship Detection - Zhen Cui et al, 2018 ACM Multimedia Conference.
- PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN - Hanwang Zhang et al, ICCV 2017. [[official Matlab code]](https://github.com/yjy941124/PPR-FCN)
- Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues - Bryan A. Plummer et al, ICCV 2017, [[official Matlab code]](https://github.com/BryanPlummer/pl-clc).
- Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation - Ruichi Yu et al, ICCV 2017.
- Weakly-supervised learning of visual relations - Julia Peyre et al, ICCV 2017, [[official Matlab code]](https://github.com/jpeyre/unrel).
- Detecting Visual Relationships with Deep Relational Networks - Bo Dai et al, CVPR 2017 oral, [[official caffe code]](https://github.com/doubledaibo/drnet_cvpr2017)
- ViP-CNN: Visual Phrase Guided Convolutional Neural Network - Yikang Li et al, CVPR 2017.
- Scene Graph Generation by Iterative Message Passing - Danfei Xu et al, CVPR 2017.
- Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection - Xiaodan Liang et al, CVPR 2017, [[pytorch]](https://github.com/nexusapoorvacus/DeepVariationStructuredRL).
- Relationship Proposal Networks - Ji Zhang et al, CVPR 2017.
- Visual Translation Embedding Network for Visual Relation Detection - Hanwang Zhang et al, CVPR 2017.
- Visual Relationship Detection with Language Priors - Lu et al, ECCV 2016 Oral, [[official Matlab code]](https://github.com/Prof-Lu-Cewu/Visual-Relationship-Detection).
- Pixels to Graphs by Associative Embedding - et al.[[offical code]](https://github.com/princeton-vl/px2graph)
- Pixels to Graphs by Associative Embedding - et al.[[offical code]](https://github.com/princeton-vl/px2graph)
- Visual Relationship Detection Based on Guided Proposals and Semantic Knowledge Distillation - François Plesse et al, ICME 2018.
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Object Recognition
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Object Detection
- Mask R-CNN - K. He et al, [[Detectron]](https://github.com/facebookresearch/Detectron), [[TensorFlow + Keras]](https://github.com/matterport/Mask_RCNN), [[MXNet]](https://github.com/TuSimple/mx-maskrcnn), [[TensorFlow]](https://github.com/CharlesShang/FastMaskRCNN), [[PyTorch]](https://github.com/felixgwu/mask_rcnn_pytorch) - State-of-the-art object detection/instance segmentation algorithm.
- Faster R-CNN - S. Ren et al, NIPS2015. [[official MatCaffe code]](https://github.com/ShaoqingRen/faster_rcnn), [[PyCaffe]](https://github.com/rbgirshick/py-faster-rcnn), [[TensorFlow]](https://github.com/smallcorgi/Faster-RCNN_TF), [[Another TF implementation]](https://github.com/CharlesShang/TFFRCNN) [[Keras]](https://github.com/yhenon/keras-frcnn) - State-of-the-art object detector.
- YOLO - J. Redmon et al, CVPR2016. [[official code]](https://github.com/pjreddie/darknet.git), [[TensorFLow]](https://github.com/gliese581gg/YOLO_tensorflow) - Fast object detector.
- YOLO9000 - J. Redmon and A. Farhadi, CVPR2017. [[official code]](https://pjreddie.com/darknet/yolo/) - State-of-the-art object detector which can detect 9000 objects in realtime.
- SSD - W. Liu et al, ECCV2016. [[official PyCaffe code]](https://github.com/weiliu89/caffe/tree/ssd), [[TensorFlow]](https://github.com/balancap/SSD-Tensorflow), [[Keras]](https://github.com/rykov8/ssd_keras) - State-of-the-art object detector with realtime processing speed.
- RetinaNet - Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He and Piotr Dollár, Facebook AI Research FAIR & ICCV 2017.[[Keras]](https://github.com/fizyr/keras-retinanet) - State-of-the-art object detector with realtime processing speed.
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Video Object Detection Datasets
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Licenses