1 citations · 3 across the 15 of their papers we have counts for
12 papers · 1 filter
DRM: Diffusion-based Reward Model With Step-wise Guidance
Jaxon Zhang, Binxin Yang, Hubery Yin +2
Current mainstream methods of aligning diffusion models with human preferences typically employ VLM-based reward models. However, these reward models, pre-trained for semantic alig…
VersusQ: Pairwise Margin Reasoning for Generalizable Video Quality Assessment
Shibei Meng, Binxin Yang, Yuan Liu +4
Large Multimodal Models (LMMs) have shown promise for video quality assessment, but most methods still predict an absolute score for each video. Such pointwise supervision often mi…
NOVA: Sparse Control, Dense Synthesis for Pair-Free Video Editing
Tianlin Pan, Jiayi Dai, Chenpu Yuan +7
Recent video editing models have achieved impressive results, but most still require large-scale paired datasets. Collecting such naturally aligned pairs at scale remains highly ch…
Improving Reconstruction of Representation Autoencoder
Siyu Liu, Chujie Qin, Hubery Yin +6
Recent work leverages Vision Foundation Models as image encoders to boost the generative performance of latent diffusion models (LDMs), as their semantic feature distributions are…
StableWorld: Towards Stable and Consistent Long Interactive Video Generation
Ying Yang, Zhengyao Lv, Yujia Zeng +9
In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds th…
DiverseAR: Boosting Diversity in Bitwise Autoregressive Image Generation
Ying Yang, Zhengyao Lv, Tianlin Pan +5
In this paper, we investigate the underexplored challenge of sample diversity in autoregressive (AR) generative models with bitwise visual tokenizers. We first analyze the factors…
FlowSteer: Guiding Few-Step Image Synthesis with Authentic Trajectories
Lei Ke, Hubery Yin, Gongye Liu +6
With the success of flow matching in visual generation, sampling efficiency remains a critical bottleneck for its practical application. Among flow models' accelerating methods, Re…
ETC: training-free diffusion models acceleration with Error-aware Trend Consistency
Jiajian Xie, Hubery Yin, Chen Li +2
Diffusion models have achieved remarkable generative quality but remain bottlenecked by costly iterative sampling. Recent training-free methods accelerate diffusion process by reus…
TimeMachine: Fine-Grained Facial Age Editing with Identity Preservation
Yilin Mi, Qixin Yan, Zheng-Peng Duan +5
With the advancement of generative models, facial image editing has made significant progress. However, achieving fine-grained age editing while preserving personal identity remain…
Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin
Fangyikang Wang, Hubery Yin, Lei Qian +9
The diffusion models (DMs) have demonstrated the remarkable capability of generating images via learning the noised score function of data distribution. Current DM sampling techniq…
BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models
Fangyikang Wang, Hubery Yin, Yuejiang Dong +5
The inversion of diffusion model sampling, which aims to find the corresponding initial noise of a sample, plays a critical role in various tasks. Recently, several heuristic exact…
Tackling the Singularities at the Endpoints of Time Intervals in Diffusion Models
Pengze Zhang, Hubery Yin, Chen Li +1
Most diffusion models assume that the reverse process adheres to a Gaussian distribution. However, this approximation has not been rigorously validated, especially at singularities…