AI for Science

Preprint Papers

Chaoqi Liang, Weiqiang Bai, Lifeng Qiao, et. al, “Rethinking the BERT-like Pretraining for DNA Sequences”, arXiv, 2023. [paper]

Tao Shen, Zhihang Hu, Zhangzhi Peng, et. al, “E2Efold-3D: End-to-End Deep Learning Method for accurate de novo RNA 3D Structure Prediction”, arXiv, 2022. [paper]

Jiayang Chen, Zhihang Hu, Siqi Sun, et. al, “Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions”, bioRxiv, 2022. [paper] [code]

Hongtai Jing, Zhengtao Gao, Sheng Xu, et. al, “Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language Model”, bioRxiv, 2023. [paper] [code]

Zhongju Yuan, Tao Shen, Sheng Xu, et. al, “AF2-Mutation: Adversarial Sequence Mutations against AlphaFold2 on Protein Tertiary Structure Prediction”, arXiv, 2023. [paper]

Le Zhang, Jiayang Chen, Tao Shen, et. al, “Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation”, arXiv, 2023. [paper] [code]

Kang Chen, Tao Han, Junchao Gong, et. al, “FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead”, arXiv, 2023. [paper]

Journal Papers

Zheqi Li, Hongjin Shi, Xueying Chen, et. al, “Nickel-Catalyzed Regio- and Enantioselective Borylative Coupling of Terminal Alkenes with Alkyl Halides Enabled by an Anionic Bisoxazoline Ligand”, Journal of the American Chemical Society (JACS) 2023, 145, 25, 13603–13614. [paper]

Dong Wu, Weiyu Kong, Yang Bao, et. al, “Alkene 1,1-difunctionalizations via organometallic-radical relay”, Nature Catalysis, 2023, 6, 11, 1030–1041. [paper]

Yaning Cui, Kang Chen, Lingyao Zhang, et. al, “Atomic Positional Embedding-Based Transformer Model for Predicting the Density of States of Crystalline Materials”, The Journal of Physical Chemistry Letters, 2023, 14, 35, 7924–7930. [paper]

Conference Papers

“The Logarithm Trick: achieve better long term forecast via Mean Logarithm Square Loss”, ICLR, 2024. [paper]

Linglin Jing, Sheng Xu, Yifan Wang, et. al, “CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding Residues”, AAAI, 2024. [paper] [code]

Zhi Jin, Sheng Xu, Xiang Zhang, et. al, “ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing”, AAAI, 2024. [paper] [code]

3D Vision

Preprint Papers

Yunhan Yang, Yukun Huang, Xiaoyang Wu, et. al, “DreamComposer: Controllable 3D Object Generation via Multi-View Conditions”, arXiv, 2023. [paper]

Yizhou Wang, Yixuan Wu, Shixiang Tang, et. al, “Hulk: A Universal Knowledge Translator for Human-Centric Tasks”, arXiv, 2023. [paper] [code]

Yan Lu, Xinzhu Ma, Lei Yang, et. al, “GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object Detection”, arXiv, 2023. [paper]

Haoyi Zhu, Honghui Yang, Xiaoyang Wu, et. al, “PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm”, arXiv, 2023. [paper] [code]

Honghui Yang, Sha Zhang, Di Huang, et. al, “UniPad: A Universal Pre-Training Paradigm For Autonomous Driving”, arXiv, 2023. [paper] [code]

Journal Papers

“Accurate Registration of Cross-Modality Geometry via Consistent Clustering”, TVCG, 2023. [paper] [code]

“Cross-source Point Cloud Registration: Challenges, Progress and Prospects”, Neurocomputing, 2023. [paper] [code]

“GMF: General Multimodal Fusion Framework for Correspondence Outlier Rejection. “, IEEE Robotics and Automation Letters, 2022. [paper]

“IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration”, IEEE Robotics and Automation Letters, 2022. [paper]

“Robust real-world point cloud registration by inlier detection”, CVIU, 2022. [paper]

“Unsupervised Point Cloud Registration by Learning Unified Gaussian Mixture Models”, IEEE Robotics and Automation Letters, 2022. [paper]

“Network Pruning via Resource Reallocation”, Pattern Recognition, 2023. [paper] [code]

Yifan Zuo, Yaping Xu, Yifeng Zeng, et. al, “A2GSTran: Depth Map Super-resolution via Asymmetric Attention with Guidance Selection”, TCSVT, 2023. [paper] [code]

Conference Papers

Xiaoshui Huang, Zhou Huang, Sheng Li, et. al, “EPCL: Frozen CLIP Transformer is An Efficient Point Cloud Encoder”, AAAI, 2024. [paper] [code]

Zhenfei Yin, Jiong Wang, Jianjian Cao, et. al, “LAMM: LanguageAssisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark”, NeurIPS, 2023. [paper]

Tianyu Huang, Bowen Dong, Yunhan Yang, et. al, “CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training”, ICCV, 2023. [paper]

Guofeng Mei, Hao Tang, Xiaoshui Huang, et. al, “Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration”, CVPR, 2023. [paper]

Mingzhi Yuan, Xiaoshui Huang, Kexue Fu, et. al, “Boosting 3D Point Cloud Registration by Transferring Multi-modality Knowledge”, ICRA, 2023. [paper] [code]

Yingjie Wang, Jiajun Deng, Yuenan Hou, et. al, “CluB: Cluster Meets BEV for LiDAR-Based 3D Object Detection”, NeurIPS, 2023. [paper]

Yeqi Bai, Ben Fei, Youquan Liu, et. al, “RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection”, NeurIPS, 2023. [paper]

Lingdong Kong, Youquan Liu, Runnan Chen, et. al, “Rethinking Range View Representation for LiDAR Segmentation”, ICCV, 2023. [paper]

Yuenan Hou, Xinge Zhu, Yuexin Ma, et. al, “Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation”, CVPR, 2023. [paper] [code]

Youquan Liu, Runnan Chen, Xin Li, et. al, “UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase”, ICCV, 2023. [paper] [code]

Zhaoyang Xia, Youquan Liu, Xin Li, et. al, “SCPNet: Semantic Scene Completion on Point Cloud”, CVPR, 2023. [paper]

Runnan Chen, Youquan Liu, Lingdong Kong, et. al, “CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP”, CVPR, 2023. [paper] [code]

Xin Li, Tao Ma, Yuenan Hou, et. al, “LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion”, CVPR, 2023. [paper] [code]

Xin Li, Botian Shi, Yuenan Hou, et. al, “Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection”, ECCV, 2022. [paper]

Guodong Xu, Yuenan Hou, Ziwei Liu, et. al, “Mind the Gap in Distilling StyleGANs”, ECCV, 2022. [paper]

Peishan Cong, Xinge Zhu, Feng Qiao, et. al, “STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes”, CVPR, 2022. [paper]

Yiteng Xu, Peishan Cong, Yichen Yao, et. al, “Human-centric Scene Understanding for 3D Large-scale Scenarios”, ICCV, 2023. [paper]

Yuhang Lu, Qi Jiang, Runnan Chen, et. al, “See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data”, ICCV, 2023. [paper]

Xiaohan Xing, Zhen Chen, Yuenan Hou, et. al, “Gradient Modulated Contrastive Distillation of Low-Rank Multi-Modal Knowledge for Disease Diagnosis”, Medical Image Analysis, 2023. [paper]

Yan Peng, Xiaogang Tang, Yiqing Zhou, et. al, “How to Tame Mobility in Federated Learning over Mobile Networks?”, IEEE Transactions on Wireless Communications, 2023. [paper]

Xiaohan Xing, Zhen Chen, Meilu Zhu, et. al, “Discrepancy and Gradient-guided Multi-modal Knowledge Distillation for Pathological Glioma Grading”, MICCAI, 2023. [paper] [code]

Di Huang, Sida Peng, Tong He, et. al, “Ponder: Point Cloud Pre-training via Neural Rendering”, ICCV, 2023. [paper]

Honghui Yang, Wenxiao Wang, Minghao Chen, et. al, “PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer”, CVPR, 2023. [paper] [code]

Honghui Yang, Tong He, Jiaheng Liu, et. al, “GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds”, CVPR, 2023. [paper] [code]

Mingye Xu, Mutian Xu, Tong He, et. al, “MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency”, CVPR, 2023. [paper]

Other Topics

2D vision, ML, LLM, etc.

Preprint Papers

Pumeng Lyu, Tao Tang, Fenghua Ling, et. al, “ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks”, arXiv, 2023. [paper]

Journals

Honghui Yang, Tong He, Jiaheng Liu, et. al, “Continuous Cross-resolution Remote Sensing Image Change Detection”, IEEE TGRS, 2023. [paper] [code]

Conferences

Tao Han, Lei Bai, Lingbo Liu, et. al, “STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning”, ICCV, 2023. [paper] [code]

Zhenfei Yin, Jiong Wang, Jianjian Cao, et. al, “LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark “, NeurIPS, 2023. [paper] [code] [demo]