Search Results for author:
Found 9 papers, 2 papers with code
Movie Gen: A Cast of Media Foundation Models
Our models set a new state-of-the-art on multiple tasks: text-to-video synthesis, video personalization, video editing, video-to-audio generation, and text-to-audio generation.
Gen2Det: Generate to Detect
In the long-tailed detection setting on LVIS, Gen2Det improves the performance on rare categories by a large margin while also significantly improving the performance on other categories, e. g. we see an improvement of 2. 13 Box AP and 1. 84 Mask AP over just training on real data on LVIS with Mask R-CNN.
GenTron: Diffusion Transformers for Image and Video Generation
In this study, we explore Transformer-based diffusion models for image and video generation.
Context Diffusion: In-Context Aware Image Generation
We propose Context Diffusion, a diffusion-based framework that enables image generation models to learn from visual examples presented in context.
Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression
Evaluation results show our method improves visual quality by 14%, prompt alignment by 16. 2% and scene diversity by 15. 3%, compared to prompt engineering the base Emu model for stickers generation.
FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning
Additionally, these works have mainly been restricted to multimodal understanding tasks.
CommerceMM: Large-Scale Commerce MultiModal Representation Learning with Omni Retrieval
We introduce CommerceMM - a multimodal model capable of providing a diverse and granular understanding of commerce topics associated to the given piece of content (image, text, image+text), and having the capability to generalize to a wide range of tasks, including Multimodal Categorization, Image-Text Retrieval, Query-to-Product Retrieval, Image-to-Product Retrieval, etc.
Large-Scale Attribute-Object Compositions
We study the problem of learning how to predict attribute-object compositions from images, and its generalization to unseen compositions missing from the training data.
Qubit Routing using Graph Neural Network aided Monte Carlo Tree Search
Near-term quantum hardware can support two-qubit operations only on the qubits that can interact with each other.
