Animating portraits using speech has received growing attention in recen...
We present a new implicit warping framework for image animation using se...
We introduce AdaViT, a method that adaptively adjusts the inference cost...
Existing conditional image synthesis frameworks generate images based on...
We present GANcraft, an unsupervised neural rendering framework for
gene...
Training deep neural networks requires gradient estimation from data bat...
We propose a neural talking-head video synthesis model and demonstrate i...
The generative adversarial network (GAN) framework has emerged as a powe...
Video-to-video synthesis (vid2vid) aims for converting high-level semant...
We introduce DeepInversion, a new method for synthesizing images from th...
Neural architecture search (NAS) aims to discover network architectures ...
Structural pruning of neural network parameters reduces computation, ene...
Relations amongst entities play a central role in image understanding. D...
Unsupervised image-to-image translation methods learn to map images in a...
This work presents a method for adding multiple tasks to a single, fixed...
This paper presents a method for adding multiple tasks to a single deep
...
This work proposes Recurrent Neural Network (RNN) models to predict
stru...
This paper presents a framework for localization or grounding of phrases...
This paper presents an approach for answering fill-in-the-blank multiple...
This paper proposes deep convolutional network models that utilize local...
We present a simple deep learning framework to simultaneously predict
ke...
Over the years, computer vision researchers have spent an immense amount...