Multiface: A Dataset for Neural Face Rendering

Along with the release of the dataset, we conduct ablation studies on the influence of different model architectures toward the model's interpolation capacity of novel viewpoint and expressions.
https://github.com/facebookresearch/multiface

Multi-scale Multi-band DenseNets for Audio Source Separation

This paper deals with the problem of audio source separation.

GitHub https://github.com/Anjok07/ultimatevocalremovergui

CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

******Large-scale datasets have played indispensable roles in the recent success of face generation/editing and significantly facilitated the advances of emerging research fields.
https://github.com/celebv-hq/celebv-hq

DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection

******As a result, DEVIANT is equivariant to the depth translations in the projective manifold whereas vanilla networks are not.
https://github.com/abhi1kumar/deviant

When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition

******Recently, most handwritten mathematical expression recognition (HMER) methods adopt the encoder-decoder networks, which directly predict the markup sequences from formula images with the attention mechanism.
https://github.com/lbh1024/can

In Defense of Online Models for Video Instance Segmentation

******In recent years, video instance segmentation (VIS) has been largely advanced by offline models, while online models gradually attracted less attention possibly due to their inferior performance.
https://github.com/wjf5203/vnext

Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild

******Omni3D re-purposes and combines existing datasets resulting in 234k images annotated with more than 3 million instances and 97 categories. 3D detection at such scale is challenging due to variations in camera intrinsics and the rich diversity of scene and object types.
https://github.com/facebookresearch/omni3d

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

📝YOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56. 8% AP among all known real-time object detectors with 30 FPS or higher on GPU V100.
https://github.com/wongkinyiu/yolov7

Generative Multiplane Images: Making a 2D GAN 3D-Aware

📝What is really needed to make an existing 2D GAN 3D-aware?
https://github.com/apple/ml-gmpi