Picture for Liang Lin

Liang Lin

Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

Dec 14, 2020
Qingxing Cao, Bailin Li, Xiaodan Liang, Keze Wang, Liang Lin

Figure 1 for Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

Figure 2 for Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

Figure 3 for Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

Figure 4 for Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

* To appear in TNNLS 2021. Considering that a desirable VQA model should correctly perceive the image context, understand the question, and incorporate its learned knowledge, our proposed dataset aims to cutoff the shortcut learning exploited by the current deep embedding models and push the research boundary of the knowledge-based visual question reasoning

Access Paper or Ask Questions

Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Dec 08, 2020
Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin

Figure 1 for Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Figure 2 for Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Figure 3 for Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Figure 4 for Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

* We introduce a large-scale RGBT benchmark for crowd counting

Access Paper or Ask Questions

A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

Oct 15, 2020
Hongjun Wang, Guanbin Li, Xiaobai Liu, Liang Lin

Figure 1 for A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

Figure 2 for A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

Figure 3 for A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

Figure 4 for A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

* Accepted as a Regular Paper in IEEE Transactions on Pattern Analysis and Machine Intelligence

Access Paper or Ask Questions

GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

Oct 08, 2020
Lishan Huang, Zheng Ye, Jinghui Qin, Liang Lin, Xiaodan Liang

Figure 1 for GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

Figure 2 for GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

Figure 3 for GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

Figure 4 for GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

* Long paper; EMNLP2020

Access Paper or Ask Questions

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Sep 25, 2020
Pengxu Wei, Hannan Lu, Radu Timofte, Liang Lin, Wangmeng Zuo, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding, Tangxin Xie, Liang Cao, Yan Zou, Yi Shen, Jialiang Zhang, Yu Jia, Kaihua Cheng, Chenhuan Wu, Yue Lin, Cen Liu, Yunbo Peng, Xueyi Zou, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Tongtong Zhao, Shanshan Zhao, Yoseob Han, Byung-Hoon Kim, JaeHyun Baek, Haoning Wu, Dejia Xu, Bo Zhou, Wei Guan, Xiaobo Li, Chen Ye, Hao Li, Haoyu Zhong, Yukai Shi, Zhijing Yang, Xiaojun Yang, Haoyu Zhong, Xin Li, Xin Jin, Yaojun Wu, Yingxue Pang, Sen Liu, Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Marie-Paule Cani, Wan-Chi Siu, Yuanbo Zhou, Rao Muhammad Umer, Christian Micheloni, Xiaofeng Cong, Rajat Gupta, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Feras Almasri, Thomas Vandamme, Olivier Debeir

Figure 1 for AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Figure 2 for AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Figure 3 for AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Figure 4 for AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

* European Conference on Computer Vision Workshops, 2020

Access Paper or Ask Questions

Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

Sep 20, 2020
Tianshui Chen, Liang Lin, Riquan Chen, Xiaolu Hui, Hefeng Wu

Figure 1 for Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

Figure 2 for Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

Figure 3 for Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

Figure 4 for Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

* Accepted at TPAMI

Access Paper or Ask Questions

Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

Sep 18, 2020
Ganlong Zhao, Guanbin Li, Ruijia Xu, Liang Lin

Figure 1 for Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

Figure 2 for Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

Figure 3 for Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

Figure 4 for Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

* Accepted by ECCV 2020

Access Paper or Ask Questions