most citedSDQM: Synthetic Data Quality Metric for Object Detection Dataset Evaluation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

9 papers

cs.CV20261 cited

SDQM: Synthetic Data Quality Metric for Object Detection Dataset Evaluation

Ayush Zenith, Arnold Zumbrun, Neel Raut +1

The performance of machine learning models depends heavily on training data. The scarcity of large-scale, well-annotated datasets poses significant challenges in creating robust mo…

cs.CV2026

HERO: Hierarchical Extrapolation and Refresh for Efficient World Models

Quanjian Song, Xinyu Wang, Donghao Zhou +3

Generation-driven world models create immersive virtual environments but suffer slow inference due to the iterative nature of diffusion models. While recent advances have improved…

cs.LG2026

Fast and Scalable Analytical Diffusion

Xinyi Shang, Peng Sun, Jingyu Lin +1

Analytical diffusion models offer a mathematically transparent path to generative modeling by formulating the denoising score as an empirical-Bayes posterior mean. However, this in…

cs.CV2025

FDP: A Frequency-Decomposition Preprocessing Pipeline for Unsupervised Anomaly Detection in Brain MRI

Hao Li, Zhenfeng Zhuang, Jingyu Lin +5

Due to the diversity of brain anatomy and the scarcity of annotated data, supervised anomaly detection for brain MRI remains challenging, driving the development of unsupervised an…

cs.CV2025

IdentityStory: Taming Your Identity-Preserving Generator for Human-Centric Story Generation

Donghao Zhou, Jingyu Lin, Guibao Shen +8

Recent visual generative models enable story generation with consistent characters from text, but human-centric story generation faces additional challenges, such as maintaining de…

cs.CV2025

SceneDecorator: Towards Scene-Oriented Story Generation with Scene Planning and Scene Consistency

Quanjian Song, Donghao Zhou, Jingyu Lin +5

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus o…