https://github.com/asukacamellia/tcpformer
공식 코드TCPFormer: Learning Temporal Correlation with Implicit Pose Proxy for 3D Human Pose Estimation
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TCPFormer: Learning Temporal Correlation with Implicit Pose Proxy for 3D Human Pose Estimation
6DoF Head Pose Estimation through Explicit Bidirectional Interaction with Face Geometry
Music for All: Representational Bias and Cross-Cultural Adaptability of Music Generation Models
GSplatLoc: Ultra-Precise Camera Localization via 3D Gaussian Splatting
AraBERT: Transformer-based Model for Arabic Language Understanding
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
Unsupervised Speech Decomposition via Triple Information Bottleneck
Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser Network
StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
DeepArUco++: Improved detection of square fiducial markers in challenging lighting conditions
AI2Agent: An End-to-End Framework for Deploying AI Projects as Autonomous Agents
Efficient Human Pose Estimation: Leveraging Advanced Techniques with MediaPipe
Deep Slow Motion Video Reconstruction with Hybrid Imaging System
Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters
Blind Image Deconvolution using Pretrained Generative Priors
WheelPoser: Sparse-IMU Based Body Pose Estimation for Wheelchair Users
Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light Conditions
Learning to Transfer Texture from Clothing Images to 3D Humans
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-Rays
Generative Adversarial Networks for Unpaired Voice Transformation on Impaired Speech
A unified one-shot prosody and speaker conversion system with self-supervised discrete speech units
Images Speak in Images: A Generalist Painter for In-Context Visual Learning
Progressive Text-to-Image Diffusion with Soft Latent Direction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.