Search Results for author: Yun Zheng

Found 20 papers, 6 papers with code

CoReS: Orchestrating the Dance of Reasoning and Segmentation

no code implementations8 Apr 2024 Xiaoyi Bao, Siyang Sun, Shuailei Ma, Kecheng Zheng, Yuxin Guo, Guosheng Zhao, Yun Zheng, Xingang Wang

We believe that the act of reasoning segmentation should mirror the cognitive stages of human visual search, where each step is a progressive refinement of thought toward the final object.

Segmentation

Automated Identification and Segmentation of Hi Sources in CRAFTS Using Deep Learning Method

1 code implementation29 Mar 2024 Zihao Song, Huaxi Chen, Donghui Quan, Di Li, Yinghui Zheng, Shulei Ni, Yunchuan Chen, Yun Zheng

We introduce a machine learning-based method for extracting HI sources from 3D spectral data, and construct a dedicated dataset of HI sources from CRAFTS.

UNET Segmentation

CrossMAE: Cross-Modality Masked Autoencoders for Region-Aware Audio-Visual Pre-Training

no code implementations CVPR 2024 Yuxin Guo, Siyang Sun, Shuailei Ma, Kecheng Zheng, Xiaoyi Bao, Shijie Ma, Wei Zou, Yun Zheng

Furthermore we dive into the mechanism of modal interaction and region alignment of CrossMAE highlighting the effectiveness of the proposed components.

Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model

no code implementations18 Dec 2023 Shuailei Ma, Chen-Wei Xie, Ying WEI, Siyang Sun, Jiaqi Fan, Xiaoyi Bao, Yuxin Guo, Yun Zheng

In this paper, we conduct a direct analysis of the multi-modal prompts by asking the following questions: $(i)$ How do the learned multi-modal prompts improve the recognition performance?

Language Modelling

Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation

no code implementations11 Dec 2023 Xiaoyi Bao, Jie Qin, Siyang Sun, Yun Zheng, Xingang Wang

To improve the semantic consistency of foreground instances, we propose an unlabeled branch as an efficient data utilization method, which teaches the model how to extract intrinsic features robust to intra-class differences.

Few-Shot Semantic Segmentation Semantic Segmentation

MomentDiff: Generative Video Moment Retrieval from Random to Real

1 code implementation NeurIPS 2023 Pandeng Li, Chen-Wei Xie, Hongtao Xie, Liming Zhao, Lei Zhang, Yun Zheng, Deli Zhao, Yongdong Zhang

Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language description.

Moment Retrieval Retrieval

Progressive Spatio-Temporal Prototype Matching for Text-Video Retrieval

1 code implementation ICCV 2023 Pandeng Li, Chen-Wei Xie, Liming Zhao, Hongtao Xie, Jiannan Ge, Yun Zheng, Deli Zhao, Yongdong Zhang

In the event-sentence prototype matching phase, we design a temporal prototype generation mechanism to associate intra-frame objects and interact inter-frame temporal relations.

Diversity Object +3

RA-CLIP: Retrieval Augmented Contrastive Language-Image Pre-Training

no code implementations CVPR 2023 Chen-Wei Xie, Siyang Sun, Xiong Xiong, Yun Zheng, Deli Zhao, Jingren Zhou

This process can be considered as an open-book exam: with the reference set as a cheat sheet, the proposed method doesn't need to memorize all visual concepts in the training data.

Classification Image Classification +5

Disentangled Representation Learning for Text-Video Retrieval

2 code implementations14 Mar 2022 Qiang Wang, Yanhao Zhang, Yun Zheng, Pan Pan, Xian-Sheng Hua

Cross-modality interaction is a critical component in Text-Video Retrieval (TVR), yet there has been little examination of how different influencing factors for computing interaction affect performance.

Ranked #10 on Video Retrieval on MSR-VTT-1kA (using extra training data)

Representation Learning Retrieval +1

Multiple Object Tracking with Correlation Learning

no code implementations CVPR 2021 Qiang Wang, Yun Zheng, Pan Pan, Yinghui Xu

Recent works have shown that convolutional networks have substantially improved the performance of multiple object tracking by simultaneously learning detection and appearance features.

Multiple Object Tracking Object +1

Few-Shot Incremental Learning with Continually Evolved Classifiers

1 code implementation CVPR 2021 Chi Zhang, Nan Song, Guosheng Lin, Yun Zheng, Pan Pan, Yinghui Xu

First, we adopt a simple but effective decoupled learning strategy of representations and classifiers that only the classifiers are updated in each incremental session, which avoids knowledge forgetting in the representations.

Few-Shot Class-Incremental Learning Incremental Learning

Large Scale Long-tailed Product Recognition System at Alibaba

no code implementations9 Feb 2021 Xiangzeng Zhou, Pan Pan, Yun Zheng, Yinghui Xu, Rong Jin

In this paper, we present a novel side information based large scale visual recognition co-training~(SICoT) system to deal with the long tail problem by leveraging the image related side information.

Object Recognition

Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance

no code implementations9 Feb 2021 Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu, Rong Jin

Benefiting from exploration of user click data, our networks are more effective to encode richer supervision and better distinguish real-shot images in terms of category and feature.

Visual Search at Alibaba

no code implementations9 Feb 2021 Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin

We hope visual search at Alibaba becomes more widely incorporated into today's commercial applications.

Image Retrieval

Large-Scale Visual Search with Binary Distributed Graph at Alibaba

no code implementations9 Feb 2021 Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin

For a deployed visual search system with several billions of online images in total, building a billion-scale offline graph in hours is essential, which is almost unachievable by most existing methods.

graph construction

Intrinsic radiation background of LaBr$_3$(Ce) detector via coincidence measurements and simulations

no code implementations15 Jul 2020 Hao Cheng, Bao-Hua Sun, Li-Hua Zhu, Tian-Xiao Li, Guang-Shuai Li, Cong-Bo Li, Xiao-Guang Wu, Yun Zheng

The LaBr$_3$(Ce) detector has attracted much attention in recent years for its superior characteristics to other scintillating materials in terms of resolution and efficiency.

Instrumentation and Detectors Nuclear Experiment

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