1 citations · 2 across the 9 of their papers we have counts for
13 papers
Glance Forcing: Making Bidirectional Diffusion Autoregressive at a Glance
Zhuobai Dong, Junchao Yi, Hu Jian Guo +3
Autoregressive generation underlies real-time, causal video synthesis and is the backbone of video world models. Today's dominant approach distills a bidirectional diffusion model…
MIND: Benchmarking Memory Consistency and Action Control in World Models
Yixuan Ye, Xuanyu Lu, Yuxin Jiang +7
World models aim to understand, remember, and predict dynamic visual environments, yet a unified benchmark for evaluating their fundamental abilities remains lacking. To address th…
Glance: Accelerating Diffusion Models with 1 Sample
Zhuobai Dong, Rui Zhao, Songjie Wu +5
Diffusion models have achieved remarkable success in image generation, yet their deployment remains constrained by the heavy computational cost and the need for numerous inference…
VideoASMR-Bench: Can AI-Generated ASMR Videos Fool VLMs and Humans?
Jiaqi Wang, Weijia Wu, Yi Zhan +6
With AI-generated videos increasingly indistinguishable from reality, current benchmarks primarily focus on broad semantic alignment and basic physical consistency, offering limite…
UniLumos: Fast and Unified Image and Video Relighting with Physics-Plausible Feedback
Ropeway Liu, Hangjie Yuan, Bo Dong +6
Relighting is a crucial task with both practical demand and artistic value, and recent diffusion models have shown strong potential by enabling rich and controllable lighting effec…
MatDecompSDF: High-Fidelity 3D Shape and PBR Material Decomposition from Multi-View Images
Chengyu Wang, Isabella Bennett, Henry Scott +4
We present MatDecompSDF, a novel framework for recovering high-fidelity 3D shapes and decomposing their physically-based material properties from multi-view images. The core challe…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
TMT: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation
Enming Zhang, Zhengyu Li, Yanru Wu +5
Recent advances in Vision Transformers (ViTs) have significantly advanced semantic segmentation performance. However, their adaptation to new target domains remains challenged by d…
Zero-Shot Human-Object Interaction Synthesis with Multimodal Priors
Yuke Lou, Yiming Wang, Zhen Wu +4
Human-object interaction (HOI) synthesis is important for various applications, ranging from virtual reality to robotics. However, acquiring 3D HOI data is challenging due to its c…
GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing
Rongyao Fang, Chengqi Duan, Kun Wang +9
Current image generation and editing methods primarily process textual prompts as direct inputs without reasoning about visual composition and explicit operations. We present Gener…
Motion Anything: Any to Motion Generation
Zeyu Zhang, Yiran Wang, Wei Mao +7
Conditional motion generation has been extensively studied in computer vision, yet two critical challenges remain. First, while masked autoregressive methods have recently outperfo…
PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
Rongyao Fang, Chengqi Duan, Kun Wang +7
Recent advancements in multimodal foundation models have yielded significant progress in vision-language understanding. Initial attempts have also explored the potential of multimo…
MOSMOS: Multi-organ segmentation facilitated by medical report supervision
Weiwei Tian, Xinyu Huang, Junlin Hou +6
Owing to a large amount of multi-modal data in modern medical systems, such as medical images and reports, Medical Vision-Language Pre-training (Med-VLP) has demonstrated incredibl…