74 citations · 158 across the 14 of their papers we have counts for
16 papers
Cosmos World Foundation Model Platform for Physical AI
NVIDIA, :, Niket Agarwal +76
Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present th…
Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models
NVIDIA, :, Yuval Atzmon +29
We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space dif…
TryOnDiffusion: A Tale of Two UNets
Luyang Zhu, Dawei Yang, Tyler Zhu +5
Given two images depicting a person and a garment worn by another person, our goal is to generate a visualization of how the garment might look on the input person. A key challenge…
HIME: Efficient Headshot Image Super-Resolution with Multiple Exemplars
Xiaoyu Xiang, Jon Morton, Fitsum A Reda +6
A promising direction for recovering the lost information in low-resolution headshot images is utilizing a set of high-resolution exemplars from the same identity. Complementary im…
Disentangling Architecture and Training for Optical Flow
Deqing Sun, Charles Herrmann, Fitsum Reda +3
How important are training details and datasets to recent optical flow models like RAFT? And do they generalize? To explore these questions, rather than develop a new model, we rev…
FILM: Frame Interpolation for Large Motion
Fitsum Reda, Janne Kontkanen, Eric Tabellion +3
We present a frame interpolation algorithm that synthesizes multiple intermediate frames from two input images with large in-between motion. Recent methods use multiple networks to…
Feature-Align Network with Knowledge Distillation for Efficient Denoising
Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan +6
We propose an efficient neural network for RAW image denoising. Although neural network-based denoising has been extensively studied for image restoration, little attention has bee…
EVRNet: Efficient Video Restoration on Edge Devices
Sachin Mehta, Amit Kumar, Fitsum Reda +4
Video transmission applications (e.g., conferencing) are gaining momentum, especially in times of global health pandemic. Video signals are transmitted over lossy channels, resulti…
Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter
Guilin Liu, Rohan Taori, Ting-Chun Wang +6
Conventional CNNs for texture synthesis consist of a sequence of (de)-convolution and up/down-sampling layers, where each layer operates locally and lacks the ability to capture th…
Neural ODEs for Image Segmentation with Level Sets
Rafael Valle, Fitsum Reda, Mohammad Shoeybi +3
We propose a novel approach for image segmentation that combines Neural Ordinary Differential Equations (NODEs) and the Level Set method. Our approach parametrizes the evolution of…
Unsupervised Video Interpolation Using Cycle Consistency
Fitsum A. Reda, Deqing Sun, Aysegul Dundar +6
Learning to synthesize high frame rate videos via interpolation requires large quantities of high frame rate training videos, which, however, are scarce, especially at high resolut…
Improving Semantic Segmentation via Video Propagation and Label Relaxation
Yi Zhu, Karan Sapra, Fitsum A. Reda +4
Semantic segmentation requires large amounts of pixel-wise annotations to learn accurate models. In this paper, we present a video prediction-based methodology to scale up training…
Partial Convolution based Padding
Guilin Liu, Kevin J. Shih, Ting-Chun Wang +5
In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks. We call it partial convolution base…
SDCNet: Video Prediction Using Spatially-Displaced Convolution
Fitsum A. Reda, Guilin Liu, Kevin J. Shih +5
We present an approach for high-resolution video frame prediction by conditioning on both past frames and past optical flows. Previous approaches rely on resampling past frames, gu…
Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu, Fitsum A. Reda, Kevin J. Shih +3
Existing deep learning based image inpainting methods use a standard convolutional network over the corrupted image, using convolutional filter responses conditioned on both valid…
Hierarchical Latent Word Clustering
Halid Ziya Yerebakan, Fitsum Reda, Yiqiang Zhan +1
This paper presents a new Bayesian non-parametric model by extending the usage of Hierarchical Dirichlet Allocation to extract tree structured word clusters from text data. The inf…