Simple Baselines for Human Pose Estimation and Tracking
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Summary
This work provides simple and effective baseline methods for pose estimation that are helpful for inspiring and evaluating new ideas for the field and achieved on challenging benchmarks.
- Type
- preprint
- Published
- 2018-04-17
- Cited by
- 2,111
- References
- 41
- Access
- Open access
- OpenAlex
- https://openalex.org/W2796779902
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4934594
Keywords
Pose, Computer science, Simple (philosophy), Baseline (sea), Code (set theory)
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
- DeepPose: Human Pose Estimation via Deep Neural Networks
- ImageNet Large Scale Visual Recognition Challenge
- Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics
- Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
- ImageNet classification with deep convolutional neural networks
- DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
- MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
- Deep Residual Learning for Image Recognition
- Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
- R-FCN: Object Detection via Region-based Fully Convolutional Networks
- Deep Feature Flow for Video Recognition
- Associative Embedding: End-to-End Learning for Joint Detection and Grouping
- Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields
- FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
- Towards Accurate Multi-person Pose Estimation in the Wild
- Deformable Convolutional Networks
- Learning Feature Pyramids for Human Pose Estimation
- PoseTrack: A Benchmark for Human Pose Estimation and Tracking
Cited by
- Effects of Image Quality on the Accuracy Human Pose Estimation and Detection of Eye Lid Opening/Closing Using Openpose and DLib
- Human Pose Regression by Combining Indirect Part Detection and Contextual Information
- JointFlow: Temporal Flow Fields for Multi Person Pose Estimation
- Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
- Localizing salient body motion in multi-person scenes using convolutional neural networks
- Revisiting Pre-training: An Efficient Training Method for Image Classification.
- Explicit Pose Deformation Learning for Tracking Human Poses
- Face detection in the operating room: comparison of state-of-the-art methods and a self-supervised approach
- CrowdPose: Efficient Crowded Scenes Pose Estimation and a New Benchmark
- Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose
- Efficient Online Multi-Person 2D Pose Tracking With Recurrent Spatio-Temporal Affinity Fields
- PoseFix: Model-Agnostic General Human Pose Refinement Network
- Action Machine: Rethinking Action Recognition in Trimmed Videos
- EANet: Enhancing Alignment for Cross-Domain Person Re-identification
- Rethinking on Multi-Stage Networks for Human Pose Estimation
- Multi-Granularity Reasoning for Social Relation Recognition From Images
- Cascade Feature Aggregation for Human Pose Estimation
- Deep High-Resolution Representation Learning for Human Pose Estimation
- Adapting RGB Pose Estimation to New Domains
- Multi‐person pose estimation using atrous convolution
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