1 citations · 2 across the 19 of their papers we have counts for
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Captain Safari: A World Engine with Pose-Aligned 3D Memory
Yu-Cheng Chou, Xingrui Wang, Yitong Li +5
World engines aim to synthesize long, 3D-consistent videos that support interactive exploration of a scene under user-controlled camera motion. However, existing systems struggle u…
World-in-World: World Models in a Closed-Loop World
Jiahan Zhang, Muqing Jiang, Nanru Dai +14
Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow embodied agents with predictive pe…
XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models
Xingrui Wang, Jiang Liu, Chao Huang +7
Omni-modal large language models (OLLMs) aim to unify audio, vision, and text understanding within a single framework. While existing benchmarks primarily evaluate general cross-mo…
EvoWorld: Evolving Panoramic World Generation with Explicit 3D Memory
Jiahao Wang, Luoxin Ye, TaiMing Lu +8
Humans possess a remarkable ability to mentally explore and replay 3D environments they have previously experienced. Inspired by this mental process, we present EvoWorld: a world m…
Autoregressive Video Generation beyond Next Frames Prediction
Sucheng Ren, Chen Chen, Zhenbang Wang +5
Autoregressive models for video generation typically operate frame-by-frame, extending next-token prediction from language to video's temporal dimension. We question that unlike wo…
Mixture of Contexts for Long Video Generation
Shengqu Cai, Ceyuan Yang, Lvmin Zhang +10
Long video generation is fundamentally a long context memory problem: models must retain and retrieve salient events across a long range without collapsing or drifting. However, sc…
Captain Cinema: Towards Short Movie Generation
Junfei Xiao, Ceyuan Yang, Lvmin Zhang +7
We present Captain Cinema, a generation framework for short movie generation. Given a detailed textual description of a movie storyline, our approach firstly generates a sequence o…
Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers
Sucheng Ren, Qihang Yu, Ju He +2
Diffusion-based Transformers have demonstrated impressive generative capabilities, but their high computational costs hinder practical deployment, for example, generating an $8192\…
ReVision: Refining Video Diffusion with Explicit 3D Motion Modeling
Qihao Liu, Ju He, Qihang Yu +2
In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges,…
Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation
Sucheng Ren, Qihang Yu, Ju He +3
Autoregressive (AR) modeling, known for its next-token prediction paradigm, underpins state-of-the-art language and visual generative models. Traditionally, a ``token'' is treated…
Dictionary-based Framework for Interpretable and Consistent Object Parsing
Tiezheng Zhang, Qihang Yu, Alan Yuille +1
In this work, we present CoCal, an interpretable and consistent object parsing framework based on dictionary-based mask transformer. Designed around Contrastive Components and Logi…
Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models
Xingrui Wang, Wufei Ma, Tiezheng Zhang +3
Although large multimodal models (LMMs) have demonstrated remarkable capabilities in visual scene interpretation and reasoning, their capacity for complex and precise 3-dimensional…
GenEx: Generating an Explorable World
Taiming Lu, Tianmin Shu, Junfei Xiao +8
Understanding, navigating, and exploring the 3D physical real world has long been a central challenge in the development of artificial intelligence. In this work, we take a step to…