Text-to-image generation has traditionally focused on finding better modeling assumptions for training on a fixed dataset.
Monster Mash is a new sketch-based modeling and animation tool that allows you to quickly sketch a character, inflate it into 3D, and promptly animate it.
The discriminator of ContraGAN discriminates the authenticity of given samples and minimizes a contrastive objective to learn the relations between training images.
Ranked #6 on
Conditional Image Generation
on CIFAR-10
(FID metric)
Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.
Unlike the recently-proposed Transformer model (e. g., ViT) that is specially designed for image classification, we propose Pyramid Vision Transformer~(PVT), which overcomes the difficulties of porting Transformer to various dense prediction tasks.
IMAGE CLASSIFICATION INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION
How do we build a general and broad object detection system?
INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION
To achieve this, we decouple appearance and motion information using a self-supervised formulation.
Ranked #1 on
Video Reconstruction
on Tai-Chi-HD
In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies.
We propose a generalization of the common Conv-layer, from a discrete layer to a Continuous Convolution (CC) Layer.
We show that the proposed model can achieve segmentation accuracies that are better than the state of the art CNNs on three datasets.