cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
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Updated
Apr 21, 2022
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cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
Official implementation of Character Region Awareness for Text Detection (CRAFT)
Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)
CVPR 论文收集,包含但不限于2022、2021、2020、2019、2018、2017文章
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
UPSNet: A Unified Panoptic Segmentation Network
Learning to Cluster Faces (CVPR 2019, CVPR 2020)
D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
Statistics and Visualization of acceptance rate, main keyword of CVPR 2019 accepted papers for the main Computer Vision conference (CVPR)
[CVPR19] FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
Project Page of 'GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction' [CVPR2019]
Code for the paper "Pose2Seg: Detection Free Human Instance Segmentation" @ CVPR2019.
Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
MSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)
Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)
[CVPR'19] 3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
Hierarchical Deep Stereo Matching on High Resolution Images, CVPR 2019.
[CVPR'19] Dataset and code used in the research project Scan2CAD: Learning CAD Model Alignment in RGB-D Scans
Official TensorFlow implementation of "PoseFix: Model-agnostic General Human Pose Refinement Network", CVPR 2019
[CVPR'19] Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks (CVPR19)
Reference ImageNet implementation of SelecSLS CNN architecture proposed in the SIGGRAPH 2020 paper "XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera". The repository also includes code for pruning the model based on implicit sparsity emerging from adaptive gradient descent methods, as detailed in the CVPR 2019 paper "On implicit filter level sparsity in Convolutional Neural Networks".
Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions. CVPR 2019
At the outset, this is a great implementation of StyleGAN in PyTorch. I really like the way the modules are structured.
This is more of a suggestion from my side:
Seems like you are not sanitizing your gradients in the code. Please check this from the official StyleGAN implementation.
I am currently
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(siammask) [liqiang@inspur siammask]$ bash test_mask_refine.sh config_vot.json SiamMask_VOT.pth VOT2016 0
[2019-03-14 19:42:16,619-rk0-test.py#551] Namespace(arch='Custom', config='config_vot.json', dataset='VOT2016', gt=False, log='log_test.txt', mask=True, refine=True, resume='SiamMask_VOT.pth', save_mask=False, visualization=False)
[2019-03-14 19:42:17,087-rk0-load_helper.py# 31] load pretrai