no code implementations • 31 Mar 2023 • Jin Liu, Xi Wang, Xiaomeng Fu, Yesheng Chai, Cai Yu, Jiao Dai, Jizhong Han
Specifically, the head pose prediction module is designed to generate head pose sequences from the source face and driving audio.
no code implementations • 16 Feb 2023 • Jin Liu, Xi Wang, Xiaomeng Fu, Yesheng Chai, Cai Yu, Jiao Dai, Jizhong Han
To solve the identity mismatch problem and achieve high-quality free pose control, we present One-shot Pose-controllable Talking head generation network (OPT).
1 code implementation • CVPR 2023 • Shaofei Huang, Zhenwei Shen, Zehao Huang, Zi-han Ding, Jiao Dai, Jizhong Han, Naiyan Wang, Si Liu
An attempt has been made to get rid of BEV and predict 3D lanes from FV representations directly, while it still underperforms other BEV-based methods given its lack of structured representation for 3D lanes.
Ranked #3 on 3D Lane Detection on Apollo Synthetic 3D Lane
1 code implementation • CVPR 2023 • Tianrui Hui, Zizheng Xun, Fengguang Peng, Junshi Huang, Xiaoming Wei, Xiaolin Wei, Jiao Dai, Jizhong Han, Si Liu
To alleviate these limitations, we propose a novel Template-Bridged Search region Interaction (TBSI) module which exploits templates as the medium to bridge the cross-modal interaction between RGB and TIR search regions by gathering and distributing target-relevant object and environment contexts.
1 code implementation • 13 Oct 2022 • Xing Wu, Chaochen Gao, Zijia Lin, Zhongyuan Wang, Jizhong Han, Songlin Hu
Sparse sampling is also likely to miss important frames corresponding to some text portions, resulting in textual redundancy.
2 code implementations • 8 Oct 2022 • Xing Wu, Chaochen Gao, Zijia Lin, Jizhong Han, Zhongyuan Wang, Songlin Hu
Contrastive learning has been extensively studied in sentence embedding learning, which assumes that the embeddings of different views of the same sentence are closer.
1 code implementation • CVPR 2022 • Zihan Ding, Tianrui Hui, Junshi Huang, Xiaoming Wei, Jizhong Han, Si Liu
Referring video object segmentation aims to predict foreground labels for objects referred by natural language expressions in videos.
2 code implementations • COLING 2022 • Xing Wu, Chaochen Gao, Yipeng Su, Jizhong Han, Zhongyuan Wang, Songlin Hu
Contrastive learning has been gradually applied to learn high-quality unsupervised sentence embedding.
2 code implementations • COLING 2022 • Xing Wu, Chaochen Gao, Liangjun Zang, Jizhong Han, Zhongyuan Wang, Songlin Hu
Unsup-SimCSE takes dropout as a minimal data augmentation method, and passes the same input sentence to a pre-trained Transformer encoder (with dropout turned on) twice to obtain the two corresponding embeddings to build a positive pair.
no code implementations • CVPR 2021 • Tianrui Hui, Shaofei Huang, Si Liu, Zihan Ding, Guanbin Li, Wenguan Wang, Jizhong Han, Fei Wang
Though 3D convolutions are amenable to recognizing which actor is performing the queried actions, it also inevitably introduces misaligned spatial information from adjacent frames, which confuses features of the target frame and yields inaccurate segmentation.
Ranked #7 on Referring Expression Segmentation on J-HMDB
no code implementations • 7 Apr 2021 • Jin Liu, Peng Chen, Tao Liang, Zhaoxing Li, Cai Yu, Shuqiao Zou, Jiao Dai, Jizhong Han
Face reenactment is a challenging task, as it is difficult to maintain accurate expression, pose and identity simultaneously.
no code implementations • 11 Jan 2021 • Shaofei Huang, Si Liu, Tianrui Hui, Jizhong Han, Bo Li, Jiashi Feng, Shuicheng Yan
Our ORDNet is able to extract more comprehensive context information and well adapt to complex spatial variance in scene images.
1 code implementation • COLING 2020 • Chunyuan Yuan, Qianwen Ma, Wei Zhou, Jizhong Han, Songlin Hu
In this way, we can explicitly exploit the credibility of publishers and users for early fake news detection.
1 code implementation • CVPR 2020 • Shaofei Huang, Tianrui Hui, Si Liu, Guanbin Li, Yunchao Wei, Jizhong Han, Luoqi Liu, Bo Li
In addition to the CMPC module, we further leverage a simple yet effective TGFE module to integrate the reasoned multimodal features from different levels with the guidance of textual information.
Ranked #10 on Referring Expression Segmentation on RefCOCO testB
1 code implementation • ECCV 2020 • Tianrui Hui, Si Liu, Shaofei Huang, Guanbin Li, Sansi Yu, Faxi Zhang, Jizhong Han
Referring image segmentation aims to predict the foreground mask of the object referred by a natural language sentence.
1 code implementation • 16 Jul 2020 • Lingwei Wei, Dou Hu, Wei Zhou, Xuehai Tang, Xiaodan Zhang, Xin Wang, Jizhong Han, Songlin Hu
Furthermore, we design a Sentiment-based Rethinking mechanism (SR) by refining the HIN with sentiment label information to learn a more sentiment-aware document representation.
no code implementations • 22 Feb 2020 • Xiaohui Song, Liangjun Zang, Yipeng Su, Xing Wu, Jizhong Han, Songlin Hu
While several state-of-the-art approaches to dialogue state tracking (DST) have shown promising performances on several benchmarks, there is still a significant performance gap between seen slot values (i. e., values that occur in both training set and test set) and unseen ones (values that occur in training set but not in test set).
1 code implementation • 9 Nov 2019 • Qianwen Ma, Chunyuan Yuan, Wei Zhou, Jizhong Han, Songlin Hu
Based on the two types of relations, we use a graph convolutional network to learn the deep correlations between styles automatically.
1 code implementation • IJCNLP 2019 • Chunyuan Yuan, Wei Zhou, Mingming Li, Shangwen Lv, Fuqing Zhu, Jizhong Han, Songlin Hu
Existing works mainly focus on matching candidate responses with every context utterance on multiple levels of granularity, which ignore the side effect of using excessive context information.
Ranked #5 on Conversational Response Selection on RRS
1 code implementation • 10 Sep 2019 • Chunyuan Yuan, Qianwen Ma, Wei Zhou, Jizhong Han, Songlin Hu
The development of social media has revolutionized the way people communicate, share information and make decisions, but it also provides an ideal platform for publishing and spreading rumors.
no code implementations • 10 Sep 2019 • Chunyuan Yuan, Wei Zhou, Qianwen Ma, Shangwen Lv, Jizhong Han, Songlin Hu
Then, we use orthogonal decomposition and fusion attention to learn a user, review, and product representation from the review information.
no code implementations • 5 Sep 2019 • Xing Wu, Dongjun Wei, Liangjun Zang, Jizhong Han, Songlin Hu
Automatic and human evaluation results show that TransSent can generate structured sentences with high quality, and has certain scalability in different tasks.
no code implementations • 21 Aug 2019 • Xing Wu, Tao Zhang, Liangjun Zang, Jizhong Han, Songlin Hu
So we propose a two step approach "Mask and Infill".
2 code implementations • 25 May 2019 • Dongjun Wei, Yaxin Liu, Fuqing Zhu, Liangjun Zang, Wei Zhou, Jizhong Han, Songlin Hu
Entity summarization aims at creating brief but informative descriptions of entities from knowledge graphs.
no code implementations • 28 Mar 2019 • Tao Zhang, Xing Wu, Meng Lin, Jizhong Han, Songlin Hu
Imbalanced data commonly exists in real world, espacially in sentiment-related corpus, making it difficult to train a classifier to distinguish latent sentiment in text data.
no code implementations • 21 Jan 2019 • Jinrong Guo, Wantao Liu, Wang Wang, Qu Lu, Songlin Hu, Jizhong Han, Ruixuan Li
Typically, Ultra-deep neural network(UDNN) tends to yield high-quality model, but its training process is usually resource intensive and time-consuming.
5 code implementations • 17 Dec 2018 • Xing Wu, Shangwen Lv, Liangjun Zang, Jizhong Han, Songlin Hu
BERT demonstrates that a deep bidirectional language model is more powerful than either an unidirectional language model or the shallow concatenation of a forward and backward model.
no code implementations • 4 Jan 2018 • Si Liu, Yao Sun, Defa Zhu, Guanghui Ren, Yu Chen, Jiashi Feng, Jizhong Han
Our proposed model explicitly learns a feature compensation network, which is specialized for mitigating the cross-domain differences.