Papers with Code 아카이브
3D Face Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wuryantoAji/POINTNET
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/wwhio/megmodels
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/xacheng1996/vfd
https://github.com/xalanq/chinese-sentiment-classification
https://github.com/xcmyz/Face-Binary-Classification
https://github.com/xcmyz/FaceDetection
https://github.com/xcmyz/Face_Binary_Classfication
https://github.com/xg416/DATUM
Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset
https://github.com/xg416/mambatm
Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset
https://github.com/xhlulu/arxiv-assistant
https://github.com/xialuxi/arcface-caffe
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
https://github.com/xiamenwcy/extended-caffe
https://github.com/xiaoccer/mobilefacenet_pytorch
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/xiaoxiong74/face-cluster-by-infomap
https://github.com/xiaoyufenfei/LEDNet
https://github.com/xilinx/finn-examples
https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters
https://github.com/xiuyu0000/papers_with_examples/tree/main/cancer_detection_demo
https://github.com/xiuyu0000/papers_with_examples/tree/main/pfld
https://github.com/xiuyu0000/tutorials/tree/main/resnet
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/resnet.py
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/xiuyu0000/vision/blob/main/mindvision/ms3d/models/pointnet2cls.py
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/xmu-xiaoma666/External-Attention-pytorch
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
https://github.com/xmu-xiaoma666/RepMLP-pytorch
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
https://github.com/xslidi/EfficientNets_ddl_apex
https://github.com/xuanyuzhou98/SqueezeSeg
https://github.com/xufanxiong/classification-of-caltech-256
https://github.com/xurui1217/pointnet.pytorch-master
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/xytpai/retinanet
https://github.com/y2kmz/pointnetv2
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/yahoo/open_nsfw
https://github.com/yakhyo/EfficientNet-PyTorch
https://github.com/yakhyo/faceboxes-pytorch
https://github.com/yakhyo/gaze-estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.