42 citations · 106 across the 12 of their papers we have counts for
12 papers
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: TREK-150 Single Object Tracking
Yuanyou Xu, Jiahao Li, Zongxin Yang +2
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object tracking and segmentation. In…
ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: Semi-Supervised Video Object Segmentation
Jiahao Li, Yuanyou Xu, Zongxin Yang +2
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object segmentation. In this study, w…
Variational Cross-Graph Reasoning and Adaptive Structured Semantics Learning for Compositional Temporal Grounding
Juncheng Li, Siliang Tang, Linchao Zhu +5
Temporal grounding is the task of locating a specific segment from an untrimmed video according to a query sentence. This task has achieved significant momentum in the computer vis…
ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022
Naiyuan Liu, Xiaohan Wang, Xiaobo Li +2
In this report, we present the ReLER@ZJU-Alibaba submission to the Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2022. Given a video clip and a text query, the goal of thi…
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence Learning
Juncheng Li, Junlin Xie, Long Qian +6
Temporal grounding in videos aims to localize one target video segment that semantically corresponds to a given query sentence. Thanks to the semantic diversity of natural language…
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images
Xiaoqiang Wang, Lei Zhu, Siliang Tang +5
Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the de…
Adaptive Hierarchical Graph Reasoning with Semantic Coherence for Video-and-Language Inference
Juncheng Li, Siliang Tang, Linchao Zhu +5
Video-and-Language Inference is a recently proposed task for joint video-and-language understanding. This new task requires a model to draw inference on whether a natural language…
SemGloVe: Semantic Co-occurrences for GloVe from BERT
Leilei Gan, Zhiyang Teng, Yue Zhang +3
GloVe learns word embeddings by leveraging statistical information from word co-occurrence matrices. However, word pairs in the matrices are extracted from a predefined local conte…
Grounded and Controllable Image Completion by Incorporating Lexical Semantics
Shengyu Zhang, Tan Jiang, Qinghao Huang +7
In this paper, we present an approach, namely Lexical Semantic Image Completion (LSIC), that may have potential applications in art, design, and heritage conservation, among severa…
Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions
Ke Ning, Linchao Zhu, Ming Cai +3
We propose a novel attentive sequence to sequence translator (ASST) for clip localization in videos by natural language descriptions. We make two contributions. First, we propose a…
An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning
Fan Wu, Zhongwen Xu, Yi Yang
We propose an end-to-end approach to the natural language object retrieval task, which localizes an object within an image according to a natural language description, i.e., referr…
Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning
Pingbo Pan, Zhongwen Xu, Yi Yang +2
Recently, deep learning approach, especially deep Convolutional Neural Networks (ConvNets), have achieved overwhelming accuracy with fast processing speed for image classification.…