activity
20172021
most citedFine-grained Discriminative Localization via Saliency-guided Faster R-CNN

39 citations · 53 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20212 cited

Video Similarity and Alignment Learning on Partial Video Copy Detection

Zhen Han, Xiangteng He, Mingqian Tang +1

Existing video copy detection methods generally measure video similarity based on spatial similarities between key frames, neglecting the latent similarity in temporal dimension, s…

cs.CV20218 cited

HANet: Hierarchical Alignment Networks for Video-Text Retrieval

Peng Wu, Xiangteng He, Mingqian Tang +2

Video-text retrieval is an important yet challenging task in vision-language understanding, which aims to learn a joint embedding space where related video and text instances are c…

cs.CV20214 cited

Self-supervised Video Retrieval Transformer Network

Xiangteng He, Yulin Pan, Mingqian Tang +1

Content-based video retrieval aims to find videos from a large video database that are similar to or even near-duplicate of a given query video. Video representation and similarity…

cs.IR2019

A New Benchmark and Approach for Fine-grained Cross-media Retrieval

Xiangteng He, Yuxin Peng, Liu Xie

Cross-media retrieval is to return the results of various media types corresponding to the query of any media type. Existing researches generally focus on coarse-grained cross-medi…

cs.CV201739 cited

Fine-grained Discriminative Localization via Saliency-guided Faster R-CNN

Xiangteng He, Yuxin Peng, Junjie Zhao

Discriminative localization is essential for fine-grained image classification task, which devotes to recognizing hundreds of subcategories in the same basic-level category. Reflec…

cs.CV2017

Fine-graind Image Classification via Combining Vision and Language

Xiangteng He, Yuxin Peng

Fine-grained image classification is a challenging task due to the large intra-class variance and small inter-class variance, aiming at recognizing hundreds of sub-categories belon…