Search Results for author: Bin Feng

Found 12 papers, 9 papers with code

Patch Aggregator for Scene Text Script Identification

no code implementations9 Dec 2019 Changxu Cheng, Qiuhui Huang, Xiang Bai, Bin Feng, Wenyu Liu

Script identification in the wild is of great importance in a multi-lingual robust-reading system.

Clustering

Maximum Entropy Regularization and Chinese Text Recognition

no code implementations9 Jul 2020 Changxu Cheng, Wuheng Xu, Xiang Bai, Bin Feng, Wenyu Liu

Chinese text recognition is more challenging than Latin text due to the large amount of fine-grained Chinese characters and the great imbalance over classes, which causes a serious overfitting problem.

Fine-Grained Image Classification

Deep multi-metric learning for text-independent speaker verification

1 code implementation17 Jul 2020 Jiwei Xu, Xinggang Wang, Bin Feng, Wenyu Liu

Text-independent speaker verification is an important artificial intelligence problem that has a wide spectrum of applications, such as criminal investigation, payment certification, and interest-based customer services.

Metric Learning Text-Independent Speaker Verification

Crossover Learning for Fast Online Video Instance Segmentation

1 code implementation ICCV 2021 Shusheng Yang, Yuxin Fang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, Wenyu Liu

For temporal information modeling in VIS, we present a novel crossover learning scheme that uses the instance feature in the current frame to pixel-wisely localize the same instance in other frames.

Instance Segmentation Semantic Segmentation +2

Instances as Queries

5 code implementations ICCV 2021 Yuxin Fang, Shusheng Yang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, Wenyu Liu

The key insight of QueryInst is to leverage the intrinsic one-to-one correspondence in object queries across different stages, as well as one-to-one correspondence between mask RoI features and object queries in the same stage.

Ranked #13 on Object Detection on COCO-O (using extra training data)

Instance Segmentation Object +4

Tracking Instances as Queries

1 code implementation22 Jun 2021 Shusheng Yang, Yuxin Fang, Xinggang Wang, Yu Li, Ying Shan, Bin Feng, Wenyu Liu

Recently, query based deep networks catch lots of attention owing to their end-to-end pipeline and competitive results on several fundamental computer vision tasks, such as object detection, semantic segmentation, and instance segmentation.

Instance Segmentation object-detection +4

Multi-scale Context-aware Network with Transformer for Gait Recognition

1 code implementation ICCV 2021 Duowang Zhu, Xiaohu Huang, Xinggang Wang, Bo Yang, Botao He, Wenyu Liu, Bin Feng

Although gait recognition has drawn increasing research attention recently, since the silhouette differences are quite subtle in spatial domain, temporal feature representation is crucial for gait recognition.

Multiview Gait Recognition Relation

Graph Contrastive Learning for Skeleton-based Action Recognition

1 code implementation26 Jan 2023 Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng

In this paper, we propose a graph contrastive learning framework for skeleton-based action recognition (\textit{SkeletonGCL}) to explore the \textit{global} context across all sequences.

Action Recognition Contrastive Learning +2

Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data

1 code implementation29 Mar 2023 Bin Feng, Tenglong Ao, Zequn Liu, Wei Ju, Libin Liu, Ming Zhang

How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task.

Disentanglement

GaitGS: Temporal Feature Learning in Granularity and Span Dimension for Gait Recognition

no code implementations31 May 2023 Haijun Xiong, Yunze Deng, Xiaohu Huang, Xinggang Wang, Wenyu Liu, Bin Feng

In order to fully harness the potential of gait recognition, it is crucial to consider temporal features at various granularities and spans.

Gait Recognition

SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM

2 code implementations6 Dec 2023 Jiayi Pan, Chengcan Wang, Kaifu Zheng, Yangguang Li, Zhenyu Wang, Bin Feng

Our results show that, with SmoothQuant+, the Code Llama-34B model can be quantized and deployed on a A100 40GB GPU, achieving lossless accuracy and a throughput increase of 1. 9 to 4. 0 times compared to the FP16 model deployed on two A100 40GB GPUs.

Quantization

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