161 citations · 387 across the 61 of their papers we have counts for
54 papers · 1 filter
Can World and Action Modeling Benefit Each Other under Unified Causal Training?
Yue Su, Bokai Lin, Xinkai Wang +9
World and action modeling are closely related, yet their reciprocal benefits under unified causal training remain unclear. We introduce OneWM, a simple framework for unified causal…
What Generation Knows: Unlocking Fine-Grained Understanding in Unified Multimodal Models
Tengju Ru, Weitong Lian, Zecong Tang +6
Fine-grained visual understanding requires distinguishing subtle differences in local attributes and spatial relations, yet remains challenging for existing vision-language models.…
Multics: Generative Multi-Player World Model with Hierarchical Communication
Kaiyi Huang, Wangbo Yu, Yukun Huang +6
Multi-player interactive world models aim to simulate shared environments from multiple players' perspectives, but achieving robust generation while scaling to more players remains…
Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget
Guoxuan Chen, Chufeng Xiao, Haoran Yang +30
We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turbo variants. It delivers compet…
GTAM: Geometry Grounded Track Anything Model
Chenming Zhu, Peizhou Cao, Jingli Lin +5
Human spatial understanding arises from jointly perceiving geometry and semantics, enabling consistent object identification and localization across viewpoints and time. Current vi…
MemLearner: Learning to Query Context memory for Video World Models
Jiwen Yu, Jianxiong Gao, Jianhong Bai +7
Video World Models are interactive video generation models that predict future world states based on user actions and history video frames. A critical challenge in video world mode…
Making Foresight Actionable: Repurposing Representation Alignment in World Action Models
Lu Qiu, Yizhuo Li, Yi Chen +3
World Action Models (WAMs) offer a promising route for robot manipulation by using video generation models to model future scene evolution before producing control actions. However…
Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators
Chenming Zhu, Jingli Lin, Yilin Long +4
While Vision-Language Models (VLMs) have shown strong visual reasoning capabilities, their spatial reasoning abilities remain largely constrained to the observed images and text-or…
From Pixels to Concepts: Do Segmentation Models Understand What They Segment?
Shuang Liang, Zeqing Wang, Yuxian Li +2
Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything Model 3 (SAM3), extend segmen…
PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World
Yunhan Yang, Chunshi Wang, Junliang Ye +7
Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on static geometry, overlookin…
Representation Forcing for Bottleneck-Free Unified Multimodal Models
Yuqing Wang, Zhijie Lin, Ceyuan Yang +10
Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrained VAE for image generation…
EgoSim: Egocentric World Simulator for Embodied Interaction Generation
Jinkun Hao, Mingda Jia, Ruiyan Wang +7
We introduce EgoSim, a closed-loop egocentric world simulator that generates spatially consistent interaction videos and persistently updates the underlying 3D scene state for cont…
OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes
Yukun Huang, Jiwen Yu, Yanning Zhou +4
There are two prevalent ways for automatic 3D scene construction: procedural generation and 2D lifting. Among these, panorama-based 2D lifting has emerged as a promising technique,…
SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models
Weiyang Jin, Yuwei Niu, Jiaqi Liao +4
Recently, remarkable progress has been made in Unified Multimodal Models (UMMs), which integrate vision-language generation and understanding capabilities within a single framework…
GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning
Yi Chen, Yuying Ge, Rui Wang +4
Recent reinforcement learning approaches, such as outcome-supervised GRPO, have advanced Chain-of-Thought reasoning in large language models (LLMs), yet their adaptation to multimo…
AnimeShooter: A Multi-Shot Animation Dataset for Reference-Guided Video Generation
Lu Qiu, Yizhuo Li, Yuying Ge +3
Recent advances in AI-generated content (AIGC) have significantly accelerated animation production. To produce engaging animations, it is essential to generate coherent multi-shot…
Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1
Yi Chen, Yuying Ge, Rui Wang +4
Recent advancements in Chain of Thought (COT) generation have significantly improved the reasoning capabilities of Large Language Models (LLMs), with reinforcement learning (RL) em…
ScanReason: Empowering 3D Visual Grounding with Reasoning Capabilities
Chenming Zhu, Tai Wang, Wenwei Zhang +2
Although great progress has been made in 3D visual grounding, current models still rely on explicit textual descriptions for grounding and lack the ability to reason human intentio…
Tailor3D: Customized 3D Assets Editing and Generation with Dual-Side Images
Zhangyang Qi, Yunhan Yang, Mengchen Zhang +7
Recent advances in 3D AIGC have shown promise in directly creating 3D objects from text and images, offering significant cost savings in animation and product design. However, deta…
T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
Kaiyue Sun, Kaiyi Huang, Xian Liu +4
Text-to-video (T2V) generative models have advanced significantly, yet their ability to compose different objects, attributes, actions, and motions into a video remains unexplored.…
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing
Zhenyu Wang, Aoxue Li, Zhenguo Li +1
Despite the success achieved by existing image generation and editing methods, current models still struggle with complex problems including intricate text prompts, and the absence…
4Diffusion: Multi-view Video Diffusion Model for 4D Generation
Haiyu Zhang, Xinyuan Chen, Yaohui Wang +3
Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeli…
DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis
Yao Teng, Yue Wu, Han Shi +5
Diffusion models have achieved great success in image generation, with the backbone evolving from U-Net to Vision Transformers. However, the computational cost of Transformers is q…
Editing Massive Concepts in Text-to-Image Diffusion Models
Tianwei Xiong, Yue Wu, Enze Xie +2
Text-to-image diffusion models suffer from the risk of generating outdated, copyrighted, incorrect, and biased content. While previous methods have mitigated the issues on a small…