1 citations · 2 across the 8 of their papers we have counts for
9 papers
InfinityStar: Unified Spacetime AutoRegressive Modeling for Visual Generation
Jinlai Liu, Jian Han, Bin Yan +6
We introduce InfinityStar, a unified spacetime autoregressive framework for high-resolution image and dynamic video synthesis. Building on the recent success of autoregressive mode…
Waver: Wave Your Way to Lifelike Video Generation
Yifu Zhang, Hao Yang, Yuqi Zhang +7
We present Waver, a high-performance foundation model for unified image and video generation. Waver can directly generate videos with durations ranging from 5 to 10 seconds at a na…
DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction
Yiheng Liu, Liao Qu, Huichao Zhang +10
This paper presents DetailFlow, a coarse-to-fine 1D autoregressive (AR) image generation method that models images through a novel next-detail prediction strategy. By learning a re…
Goku: Flow Based Video Generative Foundation Models
Shoufa Chen, Chongjian Ge, Yuqi Zhang +19
This paper introduces Goku, a state-of-the-art family of joint image-and-video generation models leveraging rectified flow Transformers to achieve industry-leading performance. We…
UniTok: A Unified Tokenizer for Visual Generation and Understanding
Chuofan Ma, Yi Jiang, Junfeng Wu +5
Visual generative and understanding models typically rely on distinct tokenizers to process images, presenting a key challenge for unifying them within a single framework. Recent s…
FlashVideo: Flowing Fidelity to Detail for Efficient High-Resolution Video Generation
Shilong Zhang, Wenbo Li, Shoufa Chen +7
DiT models have achieved great success in text-to-video generation, leveraging their scalability in model capacity and data scale. High content and motion fidelity aligned with tex…
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
Jian Han, Jinlai Liu, Yi Jiang +5
We present Infinity, a Bitwise Visual AutoRegressive Modeling capable of generating high-resolution, photorealistic images following language instruction. Infinity redefines visual…
Liquid: Language Models are Scalable and Unified Multi-modal Generators
Junfeng Wu, Yi Jiang, Chuofan Ma +5
We present Liquid, an auto-regressive generation paradigm that seamlessly integrates visual comprehension and generation by tokenizing images into discrete codes and learning these…
TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation
Liao Qu, Huichao Zhang, Yiheng Liu +7
We present TokenFlow, a novel unified image tokenizer that bridges the long-standing gap between multimodal understanding and generation. Prior research attempt to employ a single…