Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jinhui Tang, Hong-Jiang Zhang. Concurrent Multiple Instance Learning for Image Categorization, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007), Minneapolis, Minnesota, June, 2007. [pdf]
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Tao Mei, Hong-Jiang Zhang.Correlative Multi-Label Video Annotation, in ACM Multimedia 2007 (ACM MM 2007), Augsburg, Germany, Sep. 23-29, 2007. (Full Paper, Oral Presentation). Best Paper Award [pdf]
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Zheng-Jun Zha, Hong-Jiang Zhang. A Joint Appearance-Spatial Distance for Kernel-Based Image Categorization,in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, June 24-26, 2008. [pdf]
Xian-Sheng Hua, Guo-Jun Qi.Online Multi-Label Active Annotation: Towards Large-Scale Content-Based Video Search, in International ACM Conference on Multimedia 2008 (ACM MM 2008), Vancouver, Canada, October 27 - November 1, 2008. (Full Paper, Oral Presentation)
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Hong-Jiang Zhang. Two Dimensional Active Learning for Image Classification, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, June 24-26, 2008. [pdf]
Guo-Jun Qi, Xian-Sheng Hua, Hong-Jiang Zhang. Learning Semantic Distance from Community-Tagged Media Collection, in Proc. of International ACM Conference on Multimedia (ACM MM 2009), Beijing, China, October 19-24, 2009.(Full Paper, Oral Presentation) [pdf]
Guo-Jun Qi, Jinhui Tang, Zheng-Jun Zha, Tat-Seng Chua, Hong-Jiang Zhang, An Efficient Sparse Metric Learning in High-Dimensional Space via $\ell_1$-Penalized Log-Determinant Regularization, in Proc. of International Conference on Machine Learning (ICML 2009), Montreal, Quebec, June 14-18, 2009. [pdf]
Guo-Jun Qi, Qi Tian, Thomas Huang. Locality-Sensitive Support Vector Machine by Exploring Local Correlation and Global Regularization, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), Colorado Springs, Colorado, June 21-23, 2011. [pdf][code]
Guo-Jun Qi, Charu Aggarwal, Yong Rui, Qi Tian, Shiyu Chang and Thomas Huang. Towards Cross-Category Knowledge Propagation for Learning Visual Concepts, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), Colorado Springs, Colorado, June 21-23, 2011.(Oral) [pdf][code]
Guo-Jun Qi, Charu Aggarwal and Thomas Huang, Towards Semantic Knowledge Propagation from Text Corpus to Web Images, in Proc. of International World Wide Web conference (WWW 2011), Hyderabad, India, March 28-April 1, 2011. (Full Regular Paper) [pdf][code]
Guo-Jun Qi, Charu Aggarwal, Thomas Huang. Community Detection with Edge Content in Social Media Networks, in Proc. of IEEE International Conference on Data Engineering (ICDE 2012), Washington D.C., USA, April 1-5, 2012. (Full Paper)
Guo-Jun Qi, Charu Aggarwal, Thomas Huang. On Clustering Heterogeneous Social Media Objects with Outlier Links, in the fifth ACM International Conference on Web Search and Data Mining (WSDM 2012), Seattle, Washington, February 8-12, 2012.
Guo-Jun Qi, Charu Aggarwal, Thomas Huang. Transfer Learning of Distance Metrics by Cross-Domain Metric Sampling across Heterogeneous Spaces, in SIAM International Conference on Data Mining (SDM 2012), Anaheim, California, USA, April 26-28, 2012. (Full Paper)
Guo-Jun Qi, Charu Aggarwal, Thomas Huang. Online Community Detection in Social Sensing, in ACM International Conference on Web Search and Data Mining (WSDM 2013), Rome, Italy, February 4-8, 2013. [pdf]
Guo-Jun Qi, Charu Aggarwal, Thomas Huang. Link Prediction across Networks by Biased Cross-Network Sampling, in International Conference on Data Engineering (ICDE 2013), Brisbane, Australia, April 8-11, 2013. [pdf] (Full Paper) (Best ICDE 2013 Paper by IEEE Transactions on Knowledge and Data Engineering)
Guo-Jun Qi, Charu Aggarwal, Jiawei Han, Thomas Huang. Mining Collective Intelligence in Diverse Groups, to appear in Proc. of International World Wide Web conference (WWW 2013), Rio de Janeiro, Brazil, May 13th-17th, 2013. [pdf] (Full Research Paper)
Shiyu Chang§, Guo-Jun Qi, Charu Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang. Factorized Similarity Learning in Networks, in Proc. Of IEEE International Conference on Data Mining (ICDM 2014), Shenzhen, China, 2014. [pdf] (Best Student Paper)
Jun Ye§, Kai Li§, Guo-Jun Qi, Kien Hua. Temporal-Order Preserving Dynamic Quantization for Human Action Recognition from Multimodal Sensor Streams (ICMR 2015), Shanghai, China, June 23-26, 2015 (full paper). [pdf] (On UTKinect-Action dataset, our best approach has achived 100% accuracy)
Ting Zhang§, Guo-Jun Qi, Jinhui Tang, Jingdong Wang. Sparse Composite Quantization, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston, MA, June 7-12, 2015. [pdf]
Xiangbo Shu§, Guo-Jun Qi, Jinhui Tang, Jingdong Wang. Weakly-Shared Deep Transfer Networks for Heterogeneous-Domain Knowledge Propagation, in Proceedings of ACM International Conference on Multimedia (MM 2015), Brisbane, Australia, 26-30 Oct 2015. (Full Research Paper) [pdf]
Shiyu Chang§, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu Aggarwal, and Thomas Huang. Heterogeneous Network Embedding via Deep Architectures, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015. [pdf]
Vivek Veeriah§, Rohit Durvasula§, and Guo-Jun Qi*. Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015. [pdf]
Guo-Jun Qi, Charu Aggarwal, Deepak Turaga, Daby Sow and Phil Anno, State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015. [pdf]
Vivek Veeriah§, Naifan Zhuang§, and Guo-Jun Qi* . Differential Recurrent Neural Networks for Action Recognition, in Proceedings of International Conference on Computer Vision (ICCV 2015), Santiago, Chile, December 13-16, 2015. [pdf]
Hao Hu§, Joey Velez-Ginorio§, Guo-Jun Qi* . Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), San Francisco, USA, August 13-17, 2016. [pdf]
Xiaojuan Wang, Ting Zhang, Guo-Jun Qi, Jinhui Tang and Jingdong Wang. Supervised Quantization for Similarity Search, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, Nevada, USA, June 26-July 1, 2016. [pdf]
Guo-Jun Qi. Hierarchically Gated Deep Networks for Semantic Segmentation, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, Nevada, USA, June 26-July 1, 2016. (Oral Presentation, 3.9% acceptance rate) [pdf]
Junjun Jiang, Yi Yu, Suhua Tang, Jiayi Ma, Guo-Jun Qi, Akiko Aizawa, Context-patch based face hallucination via thresholding locality-constrained representation and reproducing learning, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2017), Hong Kong, China, 2017. (Finalist of the World’s First 10K Best Paper Award)
Yilin Wang, Suhang Wang, Jiliang Tang, Guo-Jun Qi, Huan Liu, Baoxin Li. CLARE: A Joint Approach to Label Classification and Tag Recommendation. in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, USA, , February 4-9, 2017.
Liheng Zhang§, Charu Aggarwal, Guo-Jun Qi*, Stock Price Prediction via Discovering Multi-Frequency Trading Patterns, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, Canada, August 13-17, 2017. [pdf] [code]
Guo-Jun Qi, Jiliang Tang, Jingdong Wang, Jiebo Luo. Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, Canada, August 13-17, 2017. [pdf]
Ting Zhang, Guo-Jun Qi, Bin Xiao, Jingdong Wang. Interleaved Group Convolutions for Deep Neural Networks, in Proceedings of International Conference on Computer Vision (ICCV 2017), Venice, Italy, October 22-29, 2017. [pdf]
Hao Hu§, Guo-Jun Qi*. State-Frequency Memory Recurrent Neural Networks, in Proceedings of International Conference on Machine Learning (ICML 2017), Sydney, Australia, August 6-11, 2017. [pdf] [code]
Guotian Xie, Jingdong Wang, Ting Zhang, Jian-Huang Lai, Richang Hong, Guo-Jun Qi. Interleaved Structured Sparse Convolutional Neural Networks, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition ( CVPR 2018), Salt Lake City, Utah, June 18th - June 22nd, 2018. [pdf]
Guo-Jun Qi, Liheng Zhang§, Hao Hu§, Marzieh Edraki§, Jingdong Wang and Xian-Sheng Hua. Global versus Localized Generative Adversarial Nets, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, Utah, June 18th - June 22nd, 2018. [pdf] [code 1: generation, code 2: semi-supervised learning]
Bin Wang§, Guo-Jun Qi, Liheng Zhang§, Lixi Deng, Yongdong Zhang. High sensitivity with tiny candidates for Pulmonary Nodule Detection, in Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention ( MICCAI 2018), Granada, Spain, September 16-20, 2018.
Yiru Zhao§, Zhongming Jin, Guo-Jun Qi, Hongtao Lu and Xian-Sheng Hua. A Principled Approach to Hard Triplet Generation via Adversarial Nets, in Proceedings of European Conference on Computer Vision (ECCV 2018), Munich, Germany, September 8 – 14, 2018.
Marzieh Edraki§, Guo-Jun Qi*. Generalized Loss-Sensitive Adversarial Learning with Manifold Margins, in Proceedings of European Conference on Computer Vision (ECCV 2018), Munich, Germany, September 8 – 14, 2018. [pdf][code: torch, blocks]
Liheng Zhang§, Marzieh Edraki§, Guo-Jun Qi*. CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces, in Proccedings of Thirty-second Conference on Neural Information Processing Systems (NeurIPS 2018), Palais des Congrès de Montréal, Montréal, Canda, December 3-8, 2018. [pdf] [code]
Muhammad Abdullah Jamal§, Guo-Jun Qi*. Task Agnostic Meta-Learning for Few-Shot Learning, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, June 16th - June 20th, 2019. [pdf]
Liheng Zhang§, Guo-Jun Qi*, Liqiang Wang, Jiebo Luo. AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, June 16th - June 20th, 2019. [pdf]
Bin Wang, Guo-Jun Qi, Sheng Tang, Tianzhu Zhang, Yunchao Wei, Linghui Li, Yongdong Zhang. Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach, International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 10-16, 2019.
Hao Hu, Liqiang Wang, Guo-Jun Qi. Learning to Adaptively Scale Recurrent Neural Networks, IN AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, Hawaii, January 27-February 1, 2019.
Zhimao Peng, Zechao Li, Junge Zhang, Yan Li, Guo-Jun Qi, Jinhui Tang. Few-Shot Image Recognition with Knowledge Transfer, in Proceedings of International Conference in Computer Vision (ICCV 2019), Seoul, Kore, Oct. 27 – Nov. 2, 2019.
Guo-Jun Qi*, Liheng Zhang, Chang Wen Chen, Qi Tian. AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations, in Proceedings of International Conference in Computer Vision (ICCV 2019), Seoul, Kore, Oct. 27 – Nov. 2, 2019. (Oral) [pdf]
Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, Hongkai Xiong, PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search, in Proceedings of International Conference on Learning Representations (ICLR 2020), Addis Ababa, Ethiopia, April 26 - 30, 2020. [pdf]
Qin Yang, Chenglin Li, Wenrui Dai, Junni Zou, Guo-Jun Qi, Hongkai Xiong. Rotation Equivariant Graph Convolutional Network for Spherical Image Classification, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020. [pdf]
Jiayu Wang, Wengang Zhou, Guo-Jun Qi, Zhongqian Fu, Qi Tian, Houqiang Li. Transformation GAN for Unsupervised Image Synthesis and Representation Learning, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020. [pdf]
Xiang Gao, Wei Hu, Guo-Jun Qi. GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020. [pdf]
Liheng Zhang, Guo-Jun Qi. WCP: Worst-Case Perturbations for Semi-Supervised Deep Learning, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020. (Oral) [pdf]
Ning Wang, Wengang Zhou, Guo-Jun Qi, Houqiang Li. POST: POlicy-Based Switch Tracking, in Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Febuary 7-12, 2020.
Tianyi Li, Guo-Jun Qi. Taxi Utilization Rate Maximization by Dynamic Demand Prediction: A Case Study in the Chicago, in Transportation Research Board (TRB) 2021 Annual Meeting, January 2021.
Xu Yang, Hanwang Zhang, Guo-Jun Qi, Jianfei Cai. Causal Attention for Vision-Language Tasks, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.
Qianjiang Hu, Xiao Wang, Wei Hu, Guo-Jun Qi*. AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.
Si Chen, Mostafa Kahla, Ruoxi Jia, Guo-Jun Qi*. Knowledge-Enriched Distributional Model Inversion Attacks, in Proceedings of IEEE/CVF Conferences on Computer Vision (ICCV 2021), Virtual, October 11 - October 17, 2021.
Ziteng Cui, Guo-Jun Qi, Lin Gu, Shaodi You, Zenghui Zhang, Tatsuya Harada. Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection, in Proceedings of IEEE/CVF Conferences on Computer Vision (ICCV 2021), Virtual, October 11 - October 17, 2021.
Feng Lin, Haohang Xu, Houqiang Li, Hongkai Xiong, Guo-Jun Qi*. Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feburary, 2021.
Xuesong Chen, Canmiao Fu, Feng Zheng, Yong Zhao, Hongsheng Li, Ping Luo, Guo-Jun Qi. A Unified Multi-Scenario Attacking Network for Visual Object Tracking, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feburary, 2021.
Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada. Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection, in Proceedings of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Isreal, October 23-27, 2022. [pdf]
Yutao Han, Youya Xia, Guo-Jun Qi, Mark Campbell. Planning Paths through Occlusions in Urban Environments, in Proceedings of Conference on Robot Learning (CoRL 2022), Auckland, New Zealand, December 14-18, 2022. [pdf]
Ce Zheng, Matias Mendieta, Taojiannan Yang, Guo-Jun Qi, Chen Chen. FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.
Ce Zheng, Xianpeng Liu, Guo-Jun Qi, Chen Chen. POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.
Zhiyuan Ma , Xiangyu Zhu, Guo-Jun Qi, Zhen Lei, Lei Zhang. OTAvatar: One-shot Talking Face Avatar with Controllable Tri-plane Rendering, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.
Tingting Liao, Xiaomei Zhang, Yuliang Xiu, Hongwei Yi, Xudong Liu, Guo-Jun Qi, Yong Zhang, Xuan Wang, Xiangyu Zhu, Zhen Lei. High-fidelity Clothed Avatar Reconstruction from a Single Image, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.
Yuelang Xu, Hongwen Zhang, Lizhen Wang, Xiaochen Zhao, Han Huang, Guo-Jun Qi, Yebin Liu. LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar, in ACM SIGGRAPH 2023 Conference Proceedings, SIGGRAPH 2023, Los Angeles, CA, USA, August 6-10, 2023. [pdf]
Benzhi Wang, Yang Yang, Jinlin Wu, Guo-Jun Qi, Zhen Lei. Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search, in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023), page 1813-1822, 2023. [pdf]
Xianpeng Liu, Ce Zheng, Kelvin B Cheng, Nan Xue, Guo-Jun Qi, Tianfu Wu. Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver, in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023), page 1813-1822, 2023. [pdf]
Yuming Qiao, Fanyi Wang, Jingwen Su, Yanhao Zhang, Yunjie Yu, Siyu Wu, Guo-Jun Qi. BARET : Balanced Attention based Real image Editing driven by Target-text Inversion, in Proceedings of The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), Vancouver, Canada, February 20-27, 2024. [pdf]
Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi. OmniMotionGPT: Animal Motion Generation with Limited Data, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2024), Seattle, USA, June 19-21, 2024. [pdf][github]
Mingyuan Zhou, Rakib Hyder, Ziwei Xuan, Guo-Jun Qi. UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2024), Seattle, USA, June 19-21, 2024. [pdf][github]
Bingwen Zhu, Fanyi Wang, Tianyi Lu, Peng Liu, Jingwen Su, Jinxiu Liu, Yanhao Zhang, Zuxuan Wu, Yu-Gang Jiang, Guo-Jun Qi. PoseAnimate: Zero-shot high fidelity pose controllable character animation, The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, August 3-9, 2024. [pdf]
Mengyi Shan, Lu Dong, Yutao Han, Yuan Yao, Tao Liu, Ifeoma Nwogu, Guo-Jun Qi and Mitchell Hill. Towards Open Domain Text-Driven Synthesis of Multi-Person Motions, in Proceedings of European Conference on Computer Vision (ECCV 2024), September 29 – October 4, MiCo Milano, 2024.
Liyuan Ma, Xueji Fang, Guo-Jun Qi. Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization, in Proceedings of ACM International Conference on Multimedia (ACM MM 2024), 28 October - 1 November 2024, Melbourne, Australia, 2024. [pdf][github]
Weijian Luo, Zemin Huang, Zhengyang Geng, J Zico Kolter, Guo-Jun Qi. One-Step Diffusion Distillation through Score Implicit Matching, in Proceedings of The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Dec 9 - Dec 15, Vancouver, Canada, 2024. [pdf][github]
Zilyu Ye, Zhiyang Chen, Tiancheng Li, Zemin Huang,Weijian Luo, Guo-Jun Qi. Schedule On the Fly: Diffusion Time Prediction for Faster and Better Image Generation, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2025), June 11 - June 15, Nashville TN, USA, 2025. [pdf][github]