Trending Research
3D Vision with Transformers: A Survey
The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field.
Deep Patch Visual Odometry
We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for monocular Visual Odometry (VO).
Reconstructing 3D Human Pose by Watching Humans in the Mirror
zju3dv/EasyMocap
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CVPR 2021
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.
Multi-scale Multi-band DenseNets for Audio Source Separation
Anjok07/ultimatevocalremovergui
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This paper deals with the problem of audio source separation.
Elucidating the Design Space of Diffusion-Based Generative Models
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.
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.
Ranked #1 on
Real-Time Object Detection
on COCO
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning
Existing model-parallel training systems either require users to manually create a parallelization plan or automatically generate one from a limited space of model parallelism configurations.
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
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
Ivy: Templated Deep Learning for Inter-Framework Portability
ivy-dl/ivy
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We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks.
Pretraining is All You Need for Image-to-Image Translation
We propose to use pretraining to boost general image-to-image translation.
Ranked #1 on
Sketch-to-Image Translation
on COCO-Stuff
