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Yitian Yuan
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2020 – today
- 2024
- [i11]Shimin Chen, Yitian Yuan, Shaoxiang Chen, Zequn Jie, Lin Ma:
Fewer Tokens and Fewer Videos: Extending Video Understanding Abilities in Large Vision-Language Models. CoRR abs/2406.08024 (2024) - [i10]Xiaoxu Xu, Yitian Yuan, Jinlong Li, Qiudan Zhang, Zequn Jie, Lin Ma, Hao Tang, Nicu Sebe, Xu Wang:
3D Weakly Supervised Semantic Segmentation with 2D Vision-Language Guidance. CoRR abs/2407.09826 (2024) - 2023
- [j5]Xiaohan Lan
, Yitian Yuan
, Xin Wang
, Zhi Wang
, Wenwu Zhu
:
A Survey on Temporal Sentence Grounding in Videos. ACM Trans. Multim. Comput. Commun. Appl. 19(2): 51:1-51:33 (2023) - [j4]Xiaohan Lan
, Yitian Yuan
, Xin Wang
, Long Chen
, Zhi Wang
, Lin Ma
, Wenwu Zhu
:
A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach. ACM Trans. Multim. Comput. Commun. Appl. 19(6): 218:1-218:23 (2023) - [c7]Xiaohan Lan, Yitian Yuan, Hong Chen, Xin Wang, Zequn Jie, Lin Ma, Zhi Wang, Wenwu Zhu:
Curriculum Multi-Negative Augmentation for Debiased Video Grounding. AAAI 2023: 1213-1221 - [i9]Xiaoxu Xu, Yitian Yuan, Qiudan Zhang, Wenhui Wu, Zequn Jie, Lin Ma, Xu Wang:
Weakly-Supervised 3D Visual Grounding based on Visual Linguistic Alignment. CoRR abs/2312.09625 (2023) - 2022
- [j3]Yitian Yuan
, Lin Ma
, Jingwen Wang, Wei Liu
, Wenwu Zhu
:
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2725-2741 (2022) - [j2]Yitian Yuan
, Lin Ma
, Wenwu Zhu
:
Syntax Customized Video Captioning by Imitating Exemplar Sentences. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10209-10221 (2022) - [i8]Xiaohan Lan, Yitian Yuan, Xin Wang, Long Chen, Zhi Wang, Lin Ma, Wenwu Zhu:
A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach. CoRR abs/2203.05243 (2022) - 2021
- [c6]Yitian Yuan, Xiaohan Lan, Xin Wang, Long Chen
, Zhi Wang, Wenwu Zhu:
A Closer Look at Temporal Sentence Grounding in Videos: Dataset and Metric. HUMA @ ACM Multimedia 2021: 13-21 - [i7]Yitian Yuan, Xiaohan Lan, Long Chen, Wei Liu, Xin Wang, Wenwu Zhu:
A Closer Look at Temporal Sentence Grounding in Videos: Datasets and Metrics. CoRR abs/2101.09028 (2021) - [i6]Xiaohan Lan, Yitian Yuan, Xin Wang, Zhi Wang, Wenwu Zhu:
A Survey on Temporal Sentence Grounding in Videos. CoRR abs/2109.08039 (2021) - [i5]Yitian Yuan, Lin Ma, Wenwu Zhu:
Syntax Customized Video Captioning by Imitating Exemplar Sentences. CoRR abs/2112.01062 (2021) - [i4]Yitian Yuan, Lin Ma, Jingwen Wang, Wenwu Zhu:
Controllable Video Captioning with an Exemplar Sentence. CoRR abs/2112.01073 (2021) - 2020
- [c5]Yitian Yuan, Lin Ma, Jingwen Wang, Wenwu Zhu:
Controllable Video Captioning with an Exemplar Sentence. ACM Multimedia 2020: 1085-1093
2010 – 2019
- 2019
- [j1]Yitian Yuan
, Tao Mei
, Peng Cui
, Wenwu Zhu
:
Video Summarization by Learning Deep Side Semantic Embedding. IEEE Trans. Circuits Syst. Video Technol. 29(1): 226-237 (2019) - [c4]Yitian Yuan, Tao Mei, Wenwu Zhu:
To Find Where You Talk: Temporal Sentence Localization in Video with Attention Based Location Regression. AAAI 2019: 9159-9166 - [c3]Yue Liu, Xin Wang, Yitian Yuan, Wenwu Zhu:
Cross-Modal Dual Learning for Sentence-to-Video Generation. ACM Multimedia 2019: 1239-1247 - [c2]Yitian Yuan, Lin Ma, Wenwu Zhu:
Sentence Specified Dynamic Video Thumbnail Generation. ACM Multimedia 2019: 2332-2340 - [c1]Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu:
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos. NeurIPS 2019: 534-544 - [i3]Yitian Yuan, Lin Ma, Wenwu Zhu:
Sentence Specified Dynamic Video Thumbnail Generation. CoRR abs/1908.04052 (2019) - [i2]Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu:
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos. CoRR abs/1910.14303 (2019) - 2018
- [i1]Yitian Yuan, Tao Mei, Wenwu Zhu:
To Find Where You Talk: Temporal Sentence Localization in Video with Attention Based Location Regression. CoRR abs/1804.07014 (2018)
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last updated on 2024-08-18 00:34 CEST by the dblp team
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