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20162024
most citedWeakly Supervised Deep Hyperspherical Quantization for Image Retrieval

13 citations · 22 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CV202413 cited

Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval

Jinpeng Wang, Bin Chen, Qiang Zhang +3

Deep quantization methods have shown high efficiency on large-scale image retrieval. However, current models heavily rely on ground-truth information, hindering the application of…

cs.CV2023

USDC: Unified Static and Dynamic Compression for Visual Transformer

Huan Yuan, Chao Liao, Jianchao Tan +5

Visual Transformers have achieved great success in almost all vision tasks, such as classification, detection, and so on. However, the model complexity and the inference speed of t…

cs.CV20231 cited

GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization

Hao Fang, Bin Chen, Xuan Wang +2

Federated Learning (FL) has recently emerged as a promising distributed machine learning framework to preserve clients' privacy, by allowing multiple clients to upload the gradient…

cs.CV20232 cited

An Adaptive Model Ensemble Adversarial Attack for Boosting Adversarial Transferability

Bin Chen, Jia-Li Yin, Shukai Chen +2

While the transferability property of adversarial examples allows the adversary to perform black-box attacks (i.e., the attacker has no knowledge about the target model), the trans…

cs.CV2023

Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers

Mingqing Wang, Jiawei Li, Zhenyang Li +4

Unsupervised anomaly detection (UAD) has been widely implemented in industrial and medical applications, which reduces the cost of manual annotation and improves efficiency in dise…

cs.CV2022

Multi-Scale Architectures Matter: On the Adversarial Robustness of Flow-based Lossless Compression

Yi-chong Xia, Bin Chen, Yan Feng +1

As a probabilistic modeling technique, the flow-based model has demonstrated remarkable potential in the field of lossless compression \cite{idf,idf++,lbb,ivpf,iflow},. Compared wi…