Context-Guided Adaptive Network for Efficient Human Pose Estimation
Authors: Lei Zhao, Jun Wen, Pengfei Wang, Nenggan Zheng3492-3499
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimenting on the COCO dataset, our method achieves 68.1 AP at 25.4 fps, and outperforms Mask R-CNN by 8.9 AP at a similar speed. The competitive performance on the HPE and person instance segmentation tasks over the state-of-the-art models show the promise of the proposed method. |
| Researcher Affiliation | Academia | 1 Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China 2 College of Computer Science and Techology, Zhejiang University, Hangzhou, China 3 Collaborative Innovation Center for Artificial Intelligence by MOE and Zhejiang Provincial Government (ZJU) 4 Zhejiang Lab, Hangzhou, China |
| Pseudocode | Yes | Algorithm 1 Dichotomy Extended Area (one box, upper boundary). |
| Open Source Code | Yes | The source code will be made available at https://github.com/zlcnup/CGANet. |
| Open Datasets | Yes | In this section, we evaluate our approach on the COCO dataset (Lin et al. 2014), which contains over 200, 000 images and 250, 000 person instances labeled with 17 keypoints. |
| Dataset Splits | Yes | It is divided into train2017/val2017/test-dev2017 sets with 57k, 5k and 20k images respectively. |
| Hardware Specification | Yes | We report the inference time (speed) of models using one batch size on the same environment equipped with a single NVIDIA GTX 2080Ti GPU |
| Software Dependencies | Yes | CUDA V10.0 and Py Torch 1.4 |
| Experiment Setup | Yes | We use data augmentation with random scale between 0.6 1.5, random rotation between 45 +45 , random translation between 40 +40 and random flip to crop an input image patch. The aligned feature sizes are 1 16, 1 32 and 1 64 of the training input size, respectively. We use the SGD optimizer for 95 epochs, with an initial learning rate of 1e-2 (dropped to 1e-3 and 1e-4 at the 70th and 85th epochs, respectively). |