https://github.com/ayushdabra/drone-images-semantic-segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
3D Face Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 9
- 보존된 평가 기록
- 94
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/ayushdabra/lunar-landscape-images-segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushdabra/retinal-oct-images-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushgupta9198/gan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushgupta9198/stylegan
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ayushpalak/darknet_cokebottles
https://github.com/ayushpalak/darknet_multi_cokebottles
https://github.com/azshue/TPT
https://github.com/b5071/pulse-rev
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/b8goal/PIRL-Residual-network
https://github.com/bailvwangzi/repulsion_loss_ssd
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/bakerv/fer-webcam
Facial Emotion Recognition: State of the Art Performance on FER2013
https://github.com/baoshengyu/deep-high-resolution-net.pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/barisbatuhan/FaceDetector
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/barmayo/spatial_attention
https://github.com/bartoszpanek1/Real-time-emotion-recognizer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/bazilas/matconvnet-deepReg
https://github.com/bclwan/MRI_Brain_Segmentation
https://github.com/becauseofAI/lffd-pytorch
https://github.com/behavioralcomputing/behaviorstructure
A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing
https://github.com/behzadhsni/BReG-NeXt
BReG-NeXt: Facial Affect Computing Using Adaptive Residual Networks With Bounded Gradient
https://github.com/beibuwandeluori/DFGC_Detection
Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/bellsrik86/DeepFaceLab
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/ben-davidson-6/fixup
https://github.com/benihime91/pytorch_retinanet
https://github.com/bennyqp/artificial-inspiration
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/bentrevett/pytorch-image-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/bepierre/SpeechVGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/bergerda1/PiFaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/bertrandlalo/deep_dog_breeds
https://github.com/beskal80/KHAIREPO
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/bethelhall/smart-attendance-system
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/bethgelab/InDomainGeneralizationBenchmark
https://github.com/bharatsush/object_detection
https://github.com/bhavinjawade/ProxyFusion-NeurIPS
https://github.com/bhavinjawade/proxyfusion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.