This paper deals with the problem of audio source separation.
In this paper, we introduce the new task of reconstructing 3D human pose from a single image in which we can see the person and the person's image through a mirror.
We argue that the theory and practice of diffusion-based generative models are currently unnecessarily convoluted and seek to remedy the situation by presenting a design space that clearly separates the concrete design choices.
Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize images of 3D scenes from novel views.
Ranked #1 on Novel View Synthesis on Mip-NeRF 360
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.
Ranked #1 on Real-Time Object Detection on COCO
We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks.
Extensive experiments demonstrate that our approach is effective and can be generalized to different video recognition scenarios.
Ranked #1 on Zero-Shot Action Recognition on Kinetics