Object Detection
cs.CV · 5 papers
DINOv2: Learning Robust Visual Features without Supervision
ImageNet-1k: 86.5%Maxime Oquab, Timothée Darcet +24
The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision.…
Momentum Contrast (MoCo)
ImageNet-1M: 60.6%Kaiming He, Haoqi Fan +3
We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic…
Masked Autoencoders Are Scalable Vision Learners
ImageNet-1K: 87.8%Kaiming He, Xinlei Chen +4
This paper shows that masked autoencoders (MAE) are scalable self-supervised learners for computer vision. Our MAE approach is simple: we mask random patches of the input image…
High-Resolution Image Synthesis with Latent Diffusion Models
FID: 5.11Robin Rombach, Andreas Blattmann +3
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image…
Deep Residual Learning for Image Recognition
Top-5 Error: 3.57%Kaiming He, Xiangyu Zhang +2
Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used…