26 citations · 59 across the 4 of their papers we have counts for
10 papers · 1 filter
VideoPoet: A Large Language Model for Zero-Shot Video Generation
Dan Kondratyuk, Lijun Yu, Xiuye Gu +28
We present VideoPoet, a language model capable of synthesizing high-quality video, with matching audio, from a large variety of conditioning signals. VideoPoet employs a decoder-on…
Advancing The Rate-Distortion-Computation Frontier For Neural Image Compression
David Minnen, Nick Johnston
The rate-distortion performance of neural image compression models has exceeded the state-of-the-art for non-learned codecs, but neural codecs are still far from widespread deploym…
Finite Scalar Quantization: VQ-VAE Made Simple
Fabian Mentzer, David Minnen, Eirikur Agustsson +1
We propose to replace vector quantization (VQ) in the latent representation of VQ-VAEs with a simple scheme termed finite scalar quantization (FSQ), where we project the VAE repres…
Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation
Lijun Yu, José Lezama, Nitesh B. Gundavarapu +13
While Large Language Models (LLMs) are the dominant models for generative tasks in language, they do not perform as well as diffusion models on image and video generation. To effec…
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
David Minnen, Johannes Ballé, George Toderici
Recent models for learned image compression are based on autoencoders, learning approximately invertible mappings from pixels to a quantized latent representation. These are combin…
Towards a Semantic Perceptual Image Metric
Troy Chinen, Johannes Ballé, Chunhui Gu +8
We present a full reference, perceptual image metric based on VGG-16, an artificial neural network trained on object classification. We fit the metric to a new database based on 14…