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20212026
most citedA Bayesian Federated Learning Framework with Online Laplace Approximation

58 citations · 123 across the 15 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024★ 1 cited

CAR: Controllable Autoregressive Modeling for Visual Generation

Ziyu Yao, Jialin Li, Yifeng Zhou +6

Controllable generation, which enables fine-grained control over generated outputs, has emerged as a critical focus in visual generative models. Currently, there are two primary te…

cs.AI2024★ 4 cited

MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection

Xi Jiang, Jian Li, Hanqiu Deng +6

In the field of industrial inspection, Multimodal Large Language Models (MLLMs) have a high potential to renew the paradigms in practical applications due to their robust language…

cs.CV2024★ 2 cited

Tuning-Free Adaptive Style Incorporation for Structure-Consistent Text-Driven Style Transfer

Yanqi Ge, Jiaqi Liu, Qingnan Fan +6

In this work, we target the task of text-driven style transfer in the context of text-to-image (T2I) diffusion models. The main challenge is consistent structure preservation while…

cs.CV2024★ 36 cited

SoftPatch: Unsupervised Anomaly Detection with Noisy Data

Xi Jiang, Ying Chen, Qiang Nie +6

Although mainstream unsupervised anomaly detection (AD) algorithms perform well in academic datasets, their performance is limited in practical application due to the ideal experim…

cs.CV2024

Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference

Xi Jiang, Ying Chen, Qiang Nie +4

In the context of high usability in single-class anomaly detection models, recent academic research has become concerned about the more complex multi-class anomaly detection. Altho…

cs.CV2024

Tuning-Free Image Customization with Image and Text Guidance

Pengzhi Li, Qiang Nie, Ying Chen +7

Despite significant advancements in image customization with diffusion models, current methods still have several limitations: 1) unintended changes in non-target areas when regene…