Papers › Autoregressive Video Generation without Vector Quantization

Autoregressive Video Generation without Vector Quantization

18 Dec 2024arXiv:2412.14169archive 2025-07-28

Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo, Yufeng Cui, Huchuan Lu, Shiguang Shan, Yonggang Qi, Xinlong Wang

This paper presents a novel approach that enables autoregressive video generation with high efficiency. We propose to reformulate the video generation problem as a non-quantized autoregressive modeling of temporal frame-by-frame prediction and spatial set-by-set prediction. Unlike raster-scan prediction in prior autoregressive models or joint distribution modeling of fixed-length tokens in diffusion models, our approach maintains the causal property of GPT-style models for flexible in-context capabilities, while leveraging bidirectional modeling within individual frames for efficiency. With the proposed approach, we train a novel video autoregressive model without vector quantization, termed NOVA. Our results demonstrate that NOVA surpasses prior autoregressive video models in data efficiency, inference speed, visual fidelity, and video fluency, even with a much smaller model capacity, i.e., 0.6B parameters. NOVA also outperforms state-of-the-art image diffusion models in text-to-image generation tasks, with a significantly lower training cost. Additionally, NOVA generalizes well across extended video durations and enables diverse zero-shot applications in one unified model. Code and models are publicly available at https://github.com/baaivision/NOVA.

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AdaLayerNorm baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository ran Apache-2.0 (permissive) · 60c4cd0d5289ebda · report
AdaLayerNormZero baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository ran Apache-2.0 (permissive) · 85377e46ac705725 · report
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VideoPosEmbed baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository ran Apache-2.0 (permissive) · f36aa3555265a176 · report
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image_decoder baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository unverified Apache-2.0 (permissive) · 7d03ff4b172aacee · report
image_encoder baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository unverified Apache-2.0 (permissive) · 9dc11e1a48d18afe · report
video_encoder baaivision/nova/diffnext/models/transformers/transformer_nova.py official repository unverified Apache-2.0 (permissive) · bb1ef5506cb864f5 · report

Tasks

Image GenerationPredictionQuantizationText to Image GenerationText-to-Image GenerationVideo Generation

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