Awesome Visual Relationship Detection:

A curated list of visual relationship detection and related area (e.g. object detection, scene graph) resources, inspired by awesome-computer-vision.

Contents

• Visual Relationship Detection
• Object Recognition

Visual Relationship Detection

Visual Relationship Detection

• NIPS 2017 - Pixels to Graphs by Associative Embedding Alejandro -et al.[offical code]

• 2018 - Attentive Relational Networks for Mapping Images to Scene Graphs Mengshi Qi et al.

• AAAI 2019 - Large-Scale Visual Relationship Understanding - Ji Zhang et al, AAAI 2019.

• 2018 - Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions - Stephan Baier et al.

• AAAI 2018 - Visual Relationship Detection with Deep Structural Ranking - Kongming Liang et al, AAAI 2018, [official pytorch=0.2.0 code].

• ECCV 2018 - Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information - Hsuan-Kung Yang et al, ECCV 2018 workshop.

• ECCV 2018 - Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features - Xu Yang et al, ECCV 2018, [tensorflow]

• CVPR 2018 - Relation Networks for Object Detection - Han Hu et al, CVPR 2018 oral paper, [official MXNet code], [pytorch].

• CVPR 2018 - Tensorize, Factorize and Regularize: Robust Visual Relationship Learning - Seong Jae Hwang et al, CVPR 2018.

• CVPR 2018 - Referring Relationships - Ranjay Krishna et al, , [official keras code].

• ICME 2018 - Visual Relationship Detection Based on Guided Proposals and Semantic Knowledge Distillation - François Plesse et al, ICME 2018.

• 2018 - Natural Language Guided Visual Relationship Detection - Wentong Liao et al.

• ACM MM 2018 - Context-Dependent Diffusion Network for Visual Relationship Detection - Zhen Cui et al, 2018 ACM Multimedia Conference.

• ICCV 2017 - PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN - Hanwang Zhang et al, ICCV 2017. [official Matlab code]

• ICCV 2017 - Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues - Bryan A. Plummer et al, ICCV 2017, [official Matlab code].

• ICCV 2017 - Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation - Ruichi Yu et al, ICCV 2017.

• ICCV 2017 - Weakly-supervised learning of visual relations - Julia Peyre et al, ICCV 2017, [official Matlab code].

• CVPR 2017 - Detecting Visual Relationships with Deep Relational Networks - Bo Dai et al, CVPR 2017 oral, [official caffe code]

• CVPR 2017 - ViP-CNN: Visual Phrase Guided Convolutional Neural Network - Yikang Li et al, CVPR 2017.

• CVPR 2017 - Scene Graph Generation by Iterative Message Passing - Danfei Xu et al, CVPR 2017.

• CVPR 2017 - Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection - Xiaodan Liang et al, CVPR 2017, [pytorch].

• CVPR 2017 - Relationship Proposal Networks - Ji Zhang et al, CVPR 2017.

• CVPR 2017 - Visual Translation Embedding Network for Visual Relation Detection - Hanwang Zhang et al, CVPR 2017.

• ECCV 2016 - Visual Relationship Detection with Language Priors - Lu et al, ECCV 2016 Oral, [official Matlab code].

Scene Graph

• CVPR 2018 - Neural Motifs: Scene Graph Parsing with Global Context - Rowan Zellers et al, CVPR 2018, [official pytorch=0.3.0 code].

• IJCAI 2018 - Representation Learning for Scene Graph Completion via Jointly Structural and Visual Embedding - Hai Wan et al, IJCAI-18.

• ICCV 2017 - Scene Graph Generation From Objects, Phrases and Region Captions - Yikang Li et al, ICCV 2017.

• CVPR 2017 - Scene Graph Generation by Iterative Message Passing - Danfei Xu et al, CVPR 2017.

Video Visual Relation Detection

• ACM MM 2017 - Video Visual Relation Detection - Xindi Shang et al, 2017 ACM Multimedia Conference, Video Visual Relation Detection

Dataset

• The Open Images Dataset V4, IJCV 2018 - The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale - Alina Kuznetsova et al, IJCV 2018.

• Visual Genome, 2016 - Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations - Ranjay Krishna et al, [official web] (https://visualgenome.org/).

• VRD, ECCV 2016 - Visual Relationship Detection with Language Priors - Lu et al, ECCV 2016 Oral.

• VidVRD, ACM MM 2017 - Video Visual Relation Dataset - Xindi Shang et al, 2018 ACM Multimedia Conference, VidVRD-helper.

Object Recognition

Object Detection

• ICCV 2017 - Deformable Convolutional Networks - J. Dai et al., ICCV 2017. [official code]

• FacebookResearch - Detectron - Open Source Object Detection Framework from Facebook AI Research. Includes Mask R-CNN, FPN, and etc. Caffe2 implementation.

• ICCV 2017 - Mask R-CNN - K. He et al, [Detectron], [TensorFlow + Keras], [MXNet], [TensorFlow], [PyTorch] - State-of-the-art object detection/instance segmentation algorithm.

• NIPS 2015 - Faster R-CNN - S. Ren et al, NIPS2015. [official MatCaffe code], [PyCaffe], [TensorFlow], [Another TF implementation] [Keras] - State-of-the-art object detector.

• CVPR 2016 - YOLO - J. Redmon et al, CVPR2016. [official code], [TensorFLow] - Fast object detector.

• CVPR 2017 - YOLO9000 - J. Redmon and A. Farhadi, CVPR2017. [official code] - State-of-the-art object detector which can detect 9000 objects in realtime.

• ECCV 2016 - SSD - W. Liu et al, ECCV2016. [official PyCaffe code], [TensorFlow], [Keras] - State-of-the-art object detector with realtime processing speed.

• ICCV 2017 - RetinaNet - Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He and Piotr Dollár, Facebook AI Research FAIR & ICCV 2017.[Keras] - State-of-the-art object detector with realtime processing speed.

Video Object Detection

• ICCV 2017 - [Detect to Track and Track to Detect] - C. Feichtenhofer et al., ICCV2017. [code], [project web]

• ICCV 2017 - [Flow-Guided Feature Aggregation for Video Object Detection] - X. Zhu et al., ICCV2017. [code], aka FGFA

Video Object Detection Datasets

• ImageNet VID

• YouTube-8M, technical report

• YouTube-BB, technical report

Licenses

License

To the extent possible under law, ALISURE has waived all copyright and related or neighboring rights to this work.

Contributing

Please feel free to send me pull requests or email ([email protected]) to add links.