Search Results for author: Chunlei Huo

Found 8 papers, 2 papers with code

Pro-tuning: Unified Prompt Tuning for Vision Tasks

no code implementations28 Jul 2022 Xing Nie, Bolin Ni, Jianlong Chang, Gaomeng Meng, Chunlei Huo, Zhaoxiang Zhang, Shiming Xiang, Qi Tian, Chunhong Pan

To this end, we propose parameter-efficient Prompt tuning (Pro-tuning) to adapt frozen vision models to various downstream vision tasks.

Adversarial Robustness Image Classification +4

TR-MISR: Multiimage Super-Resolution Based on Feature Fusion With Transformers

1 code implementation IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2022 Tai An, Xin Zhang, Chunlei Huo, Bin Xue, Lingfeng Wang, Chunhong Pan

In addition, TR-MISR adopts an additional learnable embedding vector that fuses these vectors to restore the details to the greatest extent. TR-MISR has successfully applied the transformer to MISR tasks for the first time, notably reducing the difficulty of training the transformer by ignoring the spatial relations of image patches.

Decoder Multi-Frame Super-Resolution

AME: Attention and Memory Enhancement in Hyper-Parameter Optimization

no code implementations CVPR 2022 Nuo Xu, Jianlong Chang, Xing Nie, Chunlei Huo, Shiming Xiang, Chunhong Pan

Training Deep Neural Networks (DNNs) is inherently subject to sensitive hyper-parameters and untimely feedbacks of performance evaluation.

Image Classification object-detection +2

Differentiable Convolution Search for Point Cloud Processing

no code implementations ICCV 2021 Xing Nie, Yongcheng Liu, Shaohong Chen, Jianlong Chang, Chunlei Huo, Gaofeng Meng, Qi Tian, Weiming Hu, Chunhong Pan

It can work in a purely data-driven manner and thus is capable of auto-creating a group of suitable convolutions for geometric shape modeling.

kNN Hashing With Factorized Neighborhood Representation

no code implementations ICCV 2015 Kun Ding, Chunlei Huo, Bin Fan, Chunhong Pan

Hashing is very effective for many tasks in reducing the processing time and in compressing massive databases.

Retrieval

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