45 citations · 92 across the 17 of their papers we have counts for
17 papers
Video-Language Alignment via Spatio-Temporal Graph Transformer
Shi-Xue Zhang, Hongfa Wang, Xiaobin Zhu +5
Video-language alignment is a crucial multi-modal task that benefits various downstream applications, e.g., video-text retrieval and video question answering. Existing methods eith…
Inverse-like Antagonistic Scene Text Spotting via Reading-Order Estimation and Dynamic Sampling
Shi-Xue Zhang, Chun Yang, Xiaobin Zhu +3
Scene text spotting is a challenging task, especially for inverse-like scene text, which has complex layouts, e.g., mirrored, symmetrical, or retro-flexed. In this paper, we propos…
Global and Local Semantic Completion Learning for Vision-Language Pre-training
Rong-Cheng Tu, Yatai Ji, Jie Jiang +6
Cross-modal alignment plays a crucial role in vision-language pre-training (VLP) models, enabling them to capture meaningful associations across different modalities. For this purp…
Img2Vec: A Teacher of High Token-Diversity Helps Masked AutoEncoders
Heng Pan, Chenyang Liu, Wenxiao Wang +4
We present a pipeline of Image to Vector (Img2Vec) for masked image modeling (MIM) with deep features. To study which type of deep features is appropriate for MIM as a learning tar…
Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
Yatai Ji, Rongcheng Tu, Jie Jiang +6
Cross-modal alignment is essential for vision-language pre-training (VLP) models to learn the correct corresponding information across different modalities. For this purpose, inspi…
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
Yatai Ji, Junjie Wang, Yuan Gong +6
Multimodal semantic understanding often has to deal with uncertainty, which means the obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our i…
Unsupervised Hashing with Semantic Concept Mining
Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin +5
Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is bas…
Adaptive Perception Transformer for Temporal Action Localization
Yizheng Ouyang, Tianjin Zhang, Weibo Gu +1
Temporal action localization aims to predict the boundary and category of each action instance in untrimmed long videos. Most of previous methods based on anchors or proposals negl…
DPTNet: A Dual-Path Transformer Architecture for Scene Text Detection
Jingyu Lin, Jie Jiang, Yan Yan +4
The prosperity of deep learning contributes to the rapid progress in scene text detection. Among all the methods with convolutional networks, segmentation-based ones have drawn ext…
Egocentric Video-Language Pretraining @ Ego4D Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Q…
Egocentric Video-Language Pretraining @ EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Rui Yan +9
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for the EPIC-KITCHENS-100 Multi-Instance Retrieval (MIR) challenge. Especially,…
Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization
Mengyin Liu, Chao Zhu, Hongyu Gao +4
With the prosperity of e-commerce industry, various modalities, e.g., vision and language, are utilized to describe product items. It is an enormous challenge to understand such di…
Egocentric Video-Language Pretraining
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention…
Tencent Text-Video Retrieval: Hierarchical Cross-Modal Interactions with Multi-Level Representations
Jie Jiang, Shaobo Min, Weijie Kong +4
Text-Video Retrieval plays an important role in multi-modal understanding and has attracted increasing attention in recent years. Most existing methods focus on constructing contra…
Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection
Shi-Xue Zhang, Xiaobin Zhu, Chun Yang +2
Arbitrary shape text detection is a challenging task due to the high complexity and variety of scene texts. In this work, we propose a novel adaptive boundary proposal network for…
Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection
Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou +4
Arbitrary shape text detection is a challenging task due to the high variety and complexity of scenes texts. In this paper, we propose a novel unified relational reasoning graph ne…
AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition
Chun Yang, Xu-Cheng Yin, Zejun Li +4
Recognizing text in the wild is a really challenging task because of complex backgrounds, various illuminations and diverse distortions, even with deep neural networks (convolution…