Search Results for author:
Found 26 papers, 8 papers with code
Video Editing via Factorized Diffusion Distillation
We introduce Emu Video Edit (EVE), a model that establishes a new state-of-the art in video editing without relying on any supervised video editing data.
Emu Edit: Precise Image Editing via Recognition and Generation Tasks
Lastly, to facilitate a more rigorous and informed assessment of instructable image editing models, we release a new challenging and versatile benchmark that includes seven different image editing tasks.
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
It is also a general-purpose model that can do both text-to-image and image-to-text generation, allowing us to introduce self-contained contrastive decoding methods that produce high-quality outputs.
Ranked #2 on
Text-to-Image Generation
on MS COCO
Text-To-4D Dynamic Scene Generation
We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions.
SpaText: Spatio-Textual Representation for Controllable Image Generation
Due to lack of large-scale datasets that have a detailed textual description for each region in the image, we choose to leverage the current large-scale text-to-image datasets and base our approach on a novel CLIP-based spatio-textual representation, and show its effectiveness on two state-of-the-art diffusion models: pixel-based and latent-based.
AudioGen: Textually Guided Audio Generation
Finally, we explore the ability of the proposed method to generate audio continuation conditionally and unconditionally.
Ranked #12 on
Audio Generation
on AudioCaps
Make-A-Video: Text-to-Video Generation without Text-Video Data
We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V).
Ranked #3 on
Text-to-Video Generation
on MSR-VTT
(CLIP-FID metric)
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Recent text-to-image models have achieved impressive results.
Ranked #34 on
Text-to-Image Generation
on MS COCO
Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains.
Ranked #20 on
Text-to-Image Generation
on MS COCO
(using extra training data)
High Fidelity Speech Regeneration with Application to Speech Enhancement
Speech enhancement has seen great improvement in recent years mainly through contributions in denoising, speaker separation, and dereverberation methods that mostly deal with environmental effects on vocal audio.
Unsupervised Cross-Domain Singing Voice Conversion
We present a wav-to-wav generative model for the task of singing voice conversion from any identity.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Live Face De-Identification in Video
We propose a method for face de-identification that enables fully automatic video modification at high frame rates.
Autoencoder-based Music Translation
We present a method for translating music across musical instruments and styles.
TTS Skins: Speaker Conversion via ASR
We present a fully convolutional wav-to-wav network for converting between speakers' voices, without relying on text.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Vid2Game: Controllable Characters Extracted from Real-World Videos
The second network maps the current pose, the new pose, and a given background, to an output frame.
Visual Analogies between Atari Games for Studying Transfer Learning in RL
For example, given a video frame in the target game, we map it to an analogous state in the source game and then attempt to play using a trained policy learned for the source game.
A Universal Music Translation Network
We present a method for translating music across musical instruments, genres, and styles.
Fitting New Speakers Based on a Short Untranscribed Sample
Learning-based Text To Speech systems have the potential to generalize from one speaker to the next and thus require a relatively short sample of any new voice.
VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop
We present a new neural text to speech (TTS) method that is able to transform text to speech in voices that are sampled in the wild.
Unsupervised Creation of Parameterized Avatars
We study the problem of mapping an input image to a tied pair consisting of a vector of parameters and an image that is created using a graphical engine from the vector of parameters.
Unsupervised Cross-Domain Image Generation
We study the problem of transferring a sample in one domain to an analog sample in another domain.
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues
We explore the task of recognizing peoples' identities in photo albums in an unconstrained setting.
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify.
Ranked #1 on
3D Face Modelling
on LFW
Web-Scale Training for Face Identification
Scaling machine learning methods to very large datasets has attracted considerable attention in recent years, thanks to easy access to ubiquitous sensing and data from the web.
Multi-GPU Training of ConvNets
In this work we evaluate different approaches to parallelize computation of convolutional neural networks across several GPUs.
Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition
We employ the face recognition technology developed in house at face. com to a well accepted benchmark and show that without any tuning we are able to considerably surpass state of the art results.
