Search Results for author: Teli Ma

Found 7 papers, 3 papers with code

ConvMAE: Masked Convolution Meets Masked Autoencoders

1 code implementation8 May 2022 Peng Gao, Teli Ma, Hongsheng Li, Ziyi Lin, Jifeng Dai, Yu Qiao

Masked auto-encoding for feature pretraining and multi-scale hybrid convolution-transformer architectures can further unleash the potentials of ViT, leading to state-of-the-art performances on image classification, detection and semantic segmentation.

Image Classification Object Detection +1

TerViT: An Efficient Ternary Vision Transformer

no code implementations20 Jan 2022 Sheng Xu, Yanjing Li, Teli Ma, Bohan Zeng, Baochang Zhang, Peng Gao, Jinhu Lv

Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-constrained devices.

CLIP-Adapter: Better Vision-Language Models with Feature Adapters

1 code implementation9 Oct 2021 Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, Yu Qiao

Large-scale contrastive vision-language pre-training has shown significant progress in visual representation learning.

Representation Learning

Oriented Object Detection with Transformer

no code implementations6 Jun 2021 Teli Ma, Mingyuan Mao, Honghui Zheng, Peng Gao, Xiaodi Wang, Shumin Han, Errui Ding, Baochang Zhang, David Doermann

Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN.

Object Detection

Dual-stream Network for Visual Recognition

no code implementations NeurIPS 2021 Mingyuan Mao, Renrui Zhang, Honghui Zheng, Peng Gao, Teli Ma, Yan Peng, Errui Ding, Baochang Zhang, Shumin Han

Transformers with remarkable global representation capacities achieve competitive results for visual tasks, but fail to consider high-level local pattern information in input images.

Image Classification Instance Segmentation +2

A Review of Recent Advances of Binary Neural Networks for Edge Computing

no code implementations24 Nov 2020 Wenyu Zhao, Teli Ma, Xuan Gong, Baochang Zhang, David Doermann

Edge computing is promising to become one of the next hottest topics in artificial intelligence because it benefits various evolving domains such as real-time unmanned aerial systems, industrial applications, and the demand for privacy protection.

Edge-computing Neural Architecture Search +2

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