Test Whats new message.
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
Showing 1-5 of 5 results
- Sort
Filter Results
Show
Sort By
Results
BFD: Binarized Frequency-enhanced Distillation for Vision Transformer
2024 IEEE International Conference on Multimedia and Expo (ICME)
Year: 2024 | Conference Paper |
Binarization demonstrates significant advantages in resource-limited devices, particularly for recent Vision Transformers (ViTs). To alleviate performance degradation during binarization, Knowledge Distillation (KD) is a crucial and beneficial technique. However, we identify that distilling ViTs in conventional methods overlooks high-frequency information, which loses fine-grained features and res...Show More
Spherical Centralized Quantization for Fast Image Retrieval
Jingkuan Song;Zhibin Zhang;Xiaosu Zhu;Qike Zhao;Meng Wang;Heng Tao Shen
Existing supervised quantization methods usually learn the quantizers from pair-wise, triplet, or anchor-based losses, which only capture their relationship locally without aligning them globally. This may cause an inadequate use of the entire space and a severe intersection among different semantics, leading to inferior retrieval performance. Furthermore, to enable quantizers to learn in an end-t...Show More
End-to-End Pre-Training With Hierarchical Matching and Momentum Contrast for Text-Video Retrieval
Wenxue Shen;Jingkuan Song;Xiaosu Zhu;Gongfu Li;Heng Tao Shen
Lately, video-language pre-training and text-video retrieval have attracted significant attention with the explosion of multimedia data on the Internet. However, existing approaches for video-language pre-training typically limit the exploitation of the hierarchical semantic information in videos, such as frame semantic information and global video semantic information. In this work, we present an...Show More
Revisiting Multi-Codebook Quantization
Xiaosu Zhu;Jingkuan Song;Lianli Gao;Xiaoyan Gu;Heng Tao Shen
Multi-Codebook Quantization (MCQ) is a generalized version of existing codebook-based quantizations for Approximate Nearest Neighbor (ANN) search. Specifically, MCQ picks one codeword for each sub-codebook independently and takes the sum of picked codewords to approximate the original vector. The objective function involves no constraints, therefore, MCQ theoretically has the potential to achieve ...Show More
Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression
Xiaosu Zhu;Jingkuan Song;Lianli Gao;Feng Zheng;Heng Tao Shen
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2022 | Conference Paper |
Cited by: Papers (35)
Modeling latent variables with priors and hyperpriors is an essential problem in variational image compression. Formally, trade-off between rate and distortion is handled well if priors and hyperpriors precisely describe latent variables. Current practices only adopt univariate priors and process each variable individually. However, we find inter-correlations and intra-correlations exist when obse...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.