--- My students (both advised and co-advised students) or interns are indicated by "*". ---

JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
P. Ke, H. Ji, Y. Ran, X. Cui, L. Wang, L. Song, X. Zhu, M. Huang, Findings of ACL 2021

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
L. Wang, J. Huang, Y. Li, K. Xu, Z. Yang, D. Yu, CVPR 2021

Self-Supervised 3D Mesh Reconstruction from Single Images
T. Hu, L. Wang, X. Xu, S. Liu, J. Jia, CVPR 2021

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency
X. Lai*, Z. Tian, L. Jiang, S. Liu, H. Zhao, L. Wang, J. Jia, CVPR 2021

Fully Convolutional Networks for Panoptic Segmentation
Y. Li*, H. Zhao, X. Qi, L. Wang, Z. Li, J. Sun, J. Jia, CVPR 2021 Oral

DAGN: Discourse-Aware Graph Network for Logical Reasoning
Y. Huang*, M. Fang, Y. Cao, L. Wang, X. Liang, NAACL 2021

Comprehensive Image Captioning via Scene Graph Decomposition
Y. Zhong*, L. Wang, J. Chen, D. Yu, Y. Li, ECCV 2020

Improving One-stage Visual Grounding by Recursive Sub-query Construction
Z. Yang, T. Chen, L. Wang, J. Luo, ECCV 2020

MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
J. Lei*, L. Wang, Y. Shen, D. Yu, T. Berg, M. Bansal, ACL 2020

A Fast and Accurate One-Stage Approach to Visual Grounding
Z. Yang*, B. Gong, L.Wang, W.Huang, D.Yu, J.Luo, ICCV 2019 Oral

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
K.Xu, L.Wang, M. Yu, Y. Feng, Y. Song, Z. Wang and D. Yu, ACL 2019

Diverse and Controllable Image Captioning with Part-of-Speech Guidance
A. Deshpande, J. Aneja, L. Wang, A.G.Schwing, D. A. Forsyth, CVPR 2019 Oral

Learning Structural Motif Representations For Efficient Protein Structure Search
Y.Liu, Q.Ye, L.Wang, J.Peng, ECCB, 2018

Learning Two-Branch Neural Networks for Image-Text Matching Tasks
L. Wang, Y.Li, J.Huang, S.Lazebnik, TPAMI, 2018, accepted

Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
L.Wang, A.G.Schwing, S.Lazebnik, NIPS, 2017

Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models
B. Plummer, L. Wang, C. Cervantes, J. Caicedo, J. Hockenmaier, and S. Lazebnik. IJCV, 2016, accepted.

Learning Deep Structure-Preserving Image-Text Embeddings
L.Wang, Y.Li, S.Lazebnik, CVPR, 2016

Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models
B. Plummer, L. Wang, C. Cervantes, J. Caicedo, J. Hockenmaier, S. Lazebnik, ICCV, 2015

Training Deeper Convolutional Networks with Deep Supervision
L.Wang, C.Lee, Z.Tu, S. Lazebnik, arXiv:1505.02496, 2015

Improving Image-Sentence Embeddings Using Large Weakly Annotated Photo Collections
Y. Gong, L. Wang, M. Hodosh, J. Hockenmaier, and S. Lazebnik, ECCV 2014

Multi-Scale Orderless Pooling of Deep Convolutional Activation Features
Y. Gong, L. Wang, R. Guo, and S. Lazebnik, ECCV 2014

Learning to predict from crowdsourced data
W. Bi, L. Wang, J. Kwok, and Z.Tu, UAI 2014

Discriminative Clustering via Generative Feature Mapping
L. Wang, X. Li, Z. Tu, J. Jia, AAAI 2012 Oral

Learning Sparse Covariance Patterns for Natural Scenes
L. Wang, Y. Li, J. Jia, J. Sun, D. Wipf, J. Rehg, CVPR 2012,

Bayesian Face Revisited: A Joint Formulation
D. Chen, X. Cao, L. Wang, F. Wen, J. Sun, ECCV 2012,

Learning parts-based representation for face transition
X. Li, L. Wang, H.Liu, Y.Liu, ACM MM, 2010 (* equally)