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20182024
most citedImagen Video: High Definition Video Generation with Diffusion Models

346 citations · 361 across the 5 of their papers we have counts for

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cs.CV2024

PaliGemma: A versatile 3B VLM for transfer

Lucas Beyer, Andreas Steiner, André Susano Pinto +32

PaliGemma is an open Vision-Language Model (VLM) that is based on the SigLIP-So400m vision encoder and the Gemma-2B language model. It is trained to be a versatile and broadly know…

cs.CV20241 cited

Improving fine-grained understanding in image-text pre-training

Ioana Bica, Anastasija Ilić, Matthias Bauer +8

We introduce SPARse Fine-grained Contrastive Alignment (SPARC), a simple method for pretraining more fine-grained multimodal representations from image-text pairs. Given that multi…

cs.CV2023

Video OWL-ViT: Temporally-consistent open-world localization in video

Georg Heigold, Matthias Minderer, Alexey Gritsenko +5

We present an architecture and a training recipe that adapts pre-trained open-world image models to localization in videos. Understanding the open visual world (without being const…

cs.CV202316 cited

Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution

Mostafa Dehghani, Basil Mustafa, Josip Djolonga +12

The ubiquitous and demonstrably suboptimal choice of resizing images to a fixed resolution before processing them with computer vision models has not yet been successfully challeng…

cs.CV2022346 cited

Imagen Video: High Definition Video Generation with Diffusion Models

Jonathan Ho, William Chan, Chitwan Saharia +8

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos…

cs.CV20215 cited

SCENIC: A JAX Library for Computer Vision Research and Beyond

Mostafa Dehghani, Alexey Gritsenko, Anurag Arnab +2

Scenic is an open-source JAX library with a focus on Transformer-based models for computer vision research and beyond. The goal of this toolkit is to facilitate rapid experimentati…