Can Qin

According to our database, Can Qin authored at least 53 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations.

Can Qin, Congying Xia, Krithika Ramakrishnan, Michael S. Ryoo, Lifu Tu, Yihao Feng, Manli Shu, Honglu Zhou, Anas Awadalla, Jun Wang, Senthil Purushwalkam, Le Xue, Yingbo Zhou, Huan Wang, Silvio Savarese, Juan Carlos Niebles, Zeyuan Chen, Ran Xu, Caiming Xiong

CoRR, 2024

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models.

Le Xue, Manli Shu, Anas Awadalla, Jun Wang, An Yan, Senthil Purushwalkam, Honglu Zhou, Viraj Prabhu, Yutong Dai, Michael S. Ryoo, Shrikant Kendre, Jieyu Zhang, Can Qin, Shu Zhang, Chia-Chih Chen, Ning Yu, Juntao Tan, Tulika Manoj Awalgaonkar, Shelby Heinecke, Huan Wang, Yejin Choi, Ludwig Schmidt, Zeyuan Chen, Silvio Savarese, Juan Carlos Niebles, Caiming Xiong, Ran Xu

CoRR, 2024

STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical.

Guohao Sun, Can Qin, Huazhu Fu, Linwei Wang, Zhiqiang Tao

CoRR, 2024

MuseumMaker: Continual Style Customization without Catastrophic Forgetting.

Chenxi Liu, Gan Sun, Wenqi Liang, Jiahua Dong, Can Qin, Yang Cong

CoRR, 2024

Self-Training Large Language and Vision Assistant for Medical Question Answering.

Guohao Sun, Can Qin, Huazhu Fu, Linwei Wang, Zhiqiang Tao

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant.

Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, Ran Xu, Zhiqiang Tao

Proceedings of the Computer Vision - ECCV 2024, 2024

HIVE: Harnessing Human Feedback for Instructional Visual Editing.

Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, Caiming Xiong, Ran Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

M3SOT: Multi-Frame, Multi-Field, Multi-Space 3D Single Object Tracking.

Jiaming Liu, Yue Wu, Maoguo Gong, Qiguang Miao, Wenping Ma, Cai Xu, Can Qin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Global Aligned Structured Sparsity Learning for Efficient Image Super-Resolution.

Huan Wang, Yulun Zhang, Can Qin, Luc Van Gool, Yun Fu

IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

Balancing Biases and Preserving Privacy on Balanced Faces in the Wild.

Joseph P. Robinson, Can Qin, Yann Henon, Samson Timoner, Yun Fu

IEEE Trans. Image Process., 2023

Global layout optimization of star-tree gas gathering pipeline network via an improved genetic optimization algorithm.

Jinghong Peng, Jun Zhou, Guangchuan Liang, Can Qin, Cao Peng, Yulin Chen, Chengqiang Hu

J. Intell. Fuzzy Syst., 2023

M3SOT: Multi-frame, Multi-field, Multi-space 3D Single Object Tracking.

Jiaming Liu, Yue Wu, Maoguo Gong, Qiguang Miao, Wenping Ma, Can Qin

CoRR, 2023

Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection.

Haichao Zhang, Can Qin, Yu Yin, Yun Fu

CoRR, 2023

Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning.

Huan Wang, Can Qin, Yue Bai, Yun Fu

CoRR, 2023

UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild.

Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang, Yingbo Zhou, Huan Wang, Juan Carlos Niebles, Caiming Xiong, Silvio Savarese, Stefano Ermon, Yun Fu, Ran Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Image as Set of Points.

Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Momentum is All You Need for Data-Driven Adaptive Optimization.

Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang, Yun Fu

Proceedings of the IEEE International Conference on Data Mining, 2023

GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation.

Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, Ran Xu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Mask-Free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations.

Vibashan VS, Ning Yu, Chen Xing, Can Qin, Mingfei Gao, Juan Carlos Niebles, Vishal M. Patel, Ran Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Semi-Supervised Domain Adaptive Structure Learning.

Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu

IEEE Trans. Image Process., 2022

A Close Look at Spatial Modeling: From Attention to Convolution.

Xu Ma, Huan Wang, Can Qin, Kunpeng Li, Xingchen Zhao, Jie Fu, Yun Fu

CoRR, 2022

External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters.

Can Qin, Sungchul Kim, Handong Zhao, Tong Yu, Ryan A. Rossi, Yun Fu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Recent Advances on Neural Network Pruning at Initialization.

Huan Wang, Can Qin, Yue Bai, Yulun Zhang, Yun Fu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning.

Yi Xu, Lichen Wang, Yizhou Wang, Can Qin, Yulun Zhang, Yun Fu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning.

Yulun Zhang, Huan Wang, Can Qin, Yun Fu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework.

Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Making Reconstruction-based Method Great Again for Video Anomaly Detection.

Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, Yun Fu

Proceedings of the IEEE International Conference on Data Mining, 2022

Robust Semi-supervised Domain Adaptation against Noisy Labels.

Can Qin, Yizhou Wang, Yun Fu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection.

Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Semi-Supervised Dual Relation Learning for Multi-Label Classification.

Lichen Wang, Yunyu Liu, Hang Di, Can Qin, Gan Sun, Yun Fu

IEEE Trans. Image Process., 2021

SLA²P: Self-supervised Anomaly Detection with Adversarial Perturbation.

Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu

CoRR, 2021

Adapting Stepsizes by Momentumized Gradients Improves Optimization and Generalization.

Yizhou Wang, Yue Kang, Can Qin, Yi Xu, Huan Wang, Yulun Zhang, Yun Fu

CoRR, 2021

Dynamical Isometry: The Missing Ingredient for Neural Network Pruning.

Huan Wang, Can Qin, Yue Bai, Yun Fu

CoRR, 2021

Emerging Paradigms of Neural Network Pruning.

Huan Wang, Can Qin, Yulun Zhang, Yun Fu

CoRR, 2021

Contradictory Structure Learning for Semi-supervised Domain Adaptation.

Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Aligned Structured Sparsity Learning for Efficient Image Super-Resolution.

Yulun Zhang, Huan Wang, Can Qin, Yun Fu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation.

Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis.

Yu Yin, Joseph P. Robinson, Songyao Jiang, Yue Bai, Can Qin, Yun Fu

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Neural Pruning via Growing Regularization.

Huan Wang, Can Qin, Yulun Zhang, Yun Fu

Proceedings of the 9th International Conference on Learning Representations, 2021

Aspect-based Sentiment Classification via Reinforcement Learning.

Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu

Proceedings of the IEEE International Conference on Data Mining, 2021

Context Reasoning Attention Network for Image Super-Resolution.

Yulun Zhang, Donglai Wei, Can Qin, Huan Wang, Hanspeter Pfister, Yun Fu

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces.

Joseph P. Robinson, Can Qin, Ming Shao, Matthew A. Turk, Rama Chellappa, Yun Fu

Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

2020

Semi-Supervised Hyperspectral Image Classification via Spatial-Regulated Self-Training.

Yue Wu, Guifeng Mu, Can Qin, Qiguang Miao, Wenping Ma, Xiangrong Zhang

Remote. Sens., 2020

Opposite Structure Learning for Semi-supervised Domain Adaptation.

Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu

CoRR, 2020

Deep-Learning-Enabled Simulated Annealing for Topology Optimization.

Changyu Deng, Can Qin, Wei Lu

CoRR, 2020

Generative View-Correlation Adaptation for Semi-supervised Multi-view Learning.

Yunyu Liu, Lichen Wang, Yue Bai, Can Qin, Zhengming Ding, Yun Fu

Proceedings of the Computer Vision - ECCV 2020, 2020

Face Recognition: Too Bias, or Not Too Bias?

Joseph P. Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, Samson Timoner

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Dual Relation Semi-Supervised Multi-Label Learning.

Lichen Wang, Yunyu Liu, Can Qin, Gan Sun, Yun Fu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation.

Can Qin, Haoxuan You, Lichen Wang, C.-C. Jay Kuo, Yun Fu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generatively Inferential Co-Training for Unsupervised Domain Adaptation.

Can Qin, Lichen Wang, Yulun Zhang, Yun Fu

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018

Efficient Scene Labeling via Sparse Annotations.

Can Qin, Maoguo Gong, Yue Wu, Dayong Tian, Puzhao Zhang

Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

A Multi-objective Framework for Location Recommendation Based on User Preference.

Shanfeng Wang, Maoguo Gong, Can Qin, Junwei Yang

Proceedings of the 13th International Conference on Computational Intelligence and Security, 2017

Local Probabilistic Matrix Factorization for Personal Recommendation.

Wenping Ma, Yue Wu, Maoguo Gong, Can Qin, Shanfeng Wang

Proceedings of the 13th International Conference on Computational Intelligence and Security, 2017