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20202026
most citedDual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

1 citations · 2 across the 21 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024

Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection

Haoxuan Wang, Qingdong He, Jinlong Peng +3

Open-vocabulary detection (OVD) aims to detect objects beyond a predefined set of categories. As a pioneering model incorporating the YOLO series into OVD, YOLO-World is well-suite…

cs.LG2024

Distilling Long-tailed Datasets

Zhenghao Zhao, Haoxuan Wang, Yuzhang Shang +2

Dataset distillation aims to synthesize a small, information-rich dataset from a large one for efficient model training. However, existing dataset distillation methods struggle wit…

cs.CV2024★ 1 cited

Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

Ying Jin, Jinlong Peng, Qingdong He +8

The performance of anomaly inspection in industrial manufacturing is constrained by the scarcity of anomaly data. To overcome this challenge, researchers have started employing ano…

stat.ME2024

Bayesian modeling of multi-species labeling errors in ecological studies

Haoxuan Wang, Patrik Lauha, David B. Dunson

Ecological and conservation studies monitoring bird communities typically rely on species classification based on bird vocalizations. Historically, this has been based on expert vo…

cs.CV2024

PTQ4DiT: Post-training Quantization for Diffusion Transformers

Junyi Wu, Haoxuan Wang, Yuzhang Shang +2

The recent introduction of Diffusion Transformers (DiTs) has demonstrated exceptional capabilities in image generation by using a different backbone architecture, departing from tr…

cs.CV2024

Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement

Yuxuan Gu, Yi Jin, Ben Wang +6

In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement agai…

cs.CV2024

QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Haoxuan Wang, Yuzhang Shang, Zhihang Yuan +3

The practical deployment of diffusion models is still hindered by the high memory and computational overhead. Although quantization paves a way for model compression and accelerati…