activity
20222026
most citedMaximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching

11 citations · 27 across the 32 of their papers we have counts for

collaborators
Showing cs.CVShow all

17 papers · 1 filter

cs.CV2026

Intrinsic Distribution Matching

Deyuan Liu, Yansen Han, Kaiwen Zheng +7

One-step and few-step text-to-image generation must accurately render the details specified in the prompt despite limited opportunities for refinement. Distribution matching distil…

cs.CV2026

TurboT2VA: Fast Large-Scale Text-to-Video-Audio Generation via Score-Regularized Consistency Distillation

Xiaoda Yang, Yuxiang Liu, Kaiwen Zheng +12

Joint text-to-video-audio generation produces synchronized visual and acoustic content, but the long sampling trajectories and heterogeneous multimodal computation of large models…

cs.CV2026

Vidu S1: A Real-Time Interactive Video Generation Model

Jintao Zhang, Kai Jiang, Jintao Chen +24

We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…

cs.CV2026

Causal-rCM: A Unified Teacher-Forcing and Self-Forcing Open Recipe for Autoregressive Diffusion Distillation in Streaming Video Generation and Interactive World Models

Kaiwen Zheng, Guande He, Min Zhao +7

Autoregressive video diffusion with causal diffusion transformers has emerged as a major paradigm for real-time streaming video generation and action-conditioned interactive world…

cs.CV2026

GuidedBridge: Training-freely Improving Bridge Models with Prior Guidance

Zehua Chen, Yucheng Yang, Binjie Yuan +3

Guidance methods, such as classifier-free guidance (CFG) and auto-guidance (AG), have advanced noise-to-data generation in diffusion models. Recently, bridge models have introduced…

cs.CV2026

Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation

Min Zhao, Hongzhou Zhu, Kaiwen Zheng +6

Real-time interactive video generation requires low-latency, streaming, and controllable rollout. Existing autoregressive (AR) diffusion distillation methods have achieved strong r…

cs.CV2026

minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models

Min Zhao, Hongzhou Zhu, Bokai Yan +13

Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive video world models remains…

cs.CV2025

TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times

Jintao Zhang, Kaiwen Zheng, Kai Jiang +5

We introduce TurboDiffusion, a video generation acceleration framework that can speed up end-to-end diffusion generation by 100-200x while maintaining video quality. TurboDiffusion…

cs.CV2025

World Simulation with Video Foundation Models for Physical AI

NVIDIA, :, Arslan Ali +87

We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…

cs.CV2025

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency

Kaiwen Zheng, Yuji Wang, Qianli Ma +7

Although continuous-time consistency models (e.g., sCM, MeanFlow) are theoretically principled and empirically powerful for fast academic-scale diffusion, its applicability to larg…

cs.CV2025

Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator

Kaiwen Zheng, Yongxin Chen, Huayu Chen +4

While likelihood-based generative models, particularly diffusion and autoregressive models, have achieved remarkable fidelity in visual generation, the maximum likelihood estimatio…

cs.CV2025

Visual Generation Without Guidance

Huayu Chen, Kai Jiang, Kaiwen Zheng +3

Classifier-Free Guidance (CFG) has been a default technique in various visual generative models, yet it requires inference from both conditional and unconditional models during sam…

cs.CV2024

Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model

Min Zhao, Hongzhou Zhu, Chendong Xiang +3

Diffusion models have obtained substantial progress in image-to-video generation. However, in this paper, we find that these models tend to generate videos with less motion than ex…

cs.CV2024★ 1 cited

Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models

Fan Bao, Chendong Xiang, Gang Yue +7

We introduce Vidu, a high-performance text-to-video generator that is capable of producing 1080p videos up to 16 seconds in a single generation. Vidu is a diffusion model with U-Vi…

cs.CV2023★ 2 cited

InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image

Jianhui Li, Shilong Liu, Zidong Liu +5

With the success of Neural Radiance Field (NeRF) in 3D-aware portrait editing, a variety of works have achieved promising results regarding both quality and 3D consistency. However…

cs.CV2023★ 9 cited

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics

Kaiwen Zheng, Cheng Lu, Jianfei Chen +1

Diffusion probabilistic models (DPMs) have exhibited excellent performance for high-fidelity image generation while suffering from inefficient sampling. Recent works accelerate the…

cs.CV2023

PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image

Jianhui Li, Jianmin Li, Haoji Zhang +5

We study the 3D-aware image attribute editing problem in this paper, which has wide applications in practice. Recent methods solved the problem by training a shared encoder to map…