We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for monocular Visual Odometry (VO).
The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field.
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
We propose to use pretraining to boost general image-to-image translation.
Ranked #1 on
Sketch-to-Image Translation
on COCO-Stuff