"self-supervised learning" Papers
294 papers found • Page 2 of 6
Conference
FastDINOv2: Frequency Based Curriculum Learning Improves Robustness and Training Speed
Jiaqi Zhang, Juntuo Wang, Zhixin Sun et al.
Forensic Self-Descriptions Are All You Need for Zero-Shot Detection, Open-Set Source Attribution, and Clustering of AI-generated Images
Tai Nguyen, Aref Azizpour, Matthew Stamm
GaussianOcc: Fully Self-supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting
Wanshui Gan, Fang Liu, Hongbin Xu et al.
GaussianUDF: Inferring Unsigned Distance Functions through 3D Gaussian Splatting
Shujuan Li, Yu-Shen Liu, Zhizhong Han
Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise
Brayan Monroy, Jorge Bacca, Julián Tachella
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
Tong Chen, Hao Fang, Patrick Xia et al.
Geometric Algorithms for Neural Combinatorial Optimization with Constraints
Nikolaos Karalias, Akbar Rafiey, Yifei Xu et al.
GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction
Eya Cherif, Arthur Ouaknine, Luke Brown et al.
HaHeAE: Learning Generalisable Joint Representations of Human Hand and Head Movements in Extended Reality
Zhiming Hu, Guanhua Zhang, Zheming Yin et al.
Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning
Yiyang Chen, Shanshan Zhao, Lunhao Duan et al.
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
YUJIE MO, Runpeng Yu, Xiaofeng Zhu et al.
H-MoRe: Learning Human-centric Motion Representation for Action Analysis
Zhanbo Huang, Xiaoming Liu, Yu Kong
How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations
Siddhartha Gairola, Moritz Böhle, Francesco Locatello et al.
Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings
Erel Naor, Ofir Lindenbaum
Integrating Sequence and Image Modeling in Irregular Medical Time Series Through Self-Supervised Learning
Liuqing Chen, Shuhong Xiao, Shixian Ding et al.
Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation
Jiyuan Wang, Chunyu Lin, cheng guan et al.
Joint Self-Supervised Video Alignment and Action Segmentation
Ali Shah Ali, Syed Ahmed Mahmood, Mubin Saeed et al.
Know Thyself by Knowing Others: Learning Neuron Identity from Population Context
Vinam Arora, Divyansha Lachi, Ian Knight et al.
Language Models can Self-Improve at State-Value Estimation for Better Search
Ethan Mendes, Alan Ritter
Large Self-Supervised Models Bridge the Gap in Domain Adaptive Object Detection
Marc-Antoine Lavoie, Anas Mahmoud, Steven L. Waslander
LayerLock: Non-collapsing Representation Learning with Progressive Freezing
Goker Erdogan, Nikhil Parthasarathy, Catalin Ionescu et al.
Learning from Synchronization: Self-Supervised Uncalibrated Multi-View Person Association in Challenging Scenes
Keqi Chen, vinkle srivastav, Didier MUTTER et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
Learning Valid Dual Bounds in Constraint Programming: Boosted Lagrangian Decomposition with Self-Supervised Learning
Swann Bessa, Darius Dabert, Max Bourgeat et al.
Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
Berken Utku Demirel, Christian Holz
Masked Scene Modeling: Narrowing the Gap Between Supervised and Self-Supervised Learning in 3D Scene Understanding
Pedro Hermosilla, Christian Stippel, Leon Sick
MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer
Yuancheng Wang, Haoyue Zhan, Liwei Liu et al.
MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang et al.
MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning
Wenhao Gu, Li Gu, Ching Suen et al.
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu et al.
Mitigating Spurious Features in Contrastive Learning with Spectral Regularization
Naghmeh Ghanooni, Waleed Mustafa, Dennis Wagner et al.
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
MATTHIEU CORD, Antonin Vobecky, Oriane Siméoni et al.
ModalTune: Fine-Tuning Slide-Level Foundation Models with Multi-Modal Information for Multi-task Learning in Digital Pathology
Vishwesh Ramanathan, Tony Xu, Pushpak Pati et al.
MoE-Gyro: Self-Supervised Over-Range Reconstruction and Denoising for MEMS Gyroscopes
Feiyang Pan, Shenghe Zheng, Chunyan Yin et al.
MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition
Hao Zhang, Zhan Zhuang, Xuehao Wang et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
MoSiC: Optimal-Transport Motion Trajectory for Dense Self-Supervised Learning
Mohammadreza Salehi, Shashanka Venkataramanan, Ioana Simion et al.
M-SpecGene: Generalized Foundation Model for RGBT Multispectral Vision
Kailai Zhou, Fuqiang Yang, Shixian Wang et al.
Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning
Sheng Li, Qitao Tan, Yue Dai et al.
Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving
Peidong Li, Dixiao Cui
Neural Eulerian Scene Flow Fields
Kyle Vedder, Neehar Peri, Ishan Khatri et al.
Noise Modeling in One Hour: Minimizing Preparation Efforts for Self-supervised Low-Light RAW Image Denoising
Feiran Li, Haiyang Jiang, Daisuke Iso
Noisy Node Classification by Bi-level Optimization Based Multi-Teacher Distillation
Yujing Liu, Zongqian Wu, Zhengyu Lu et al.
Not All Data are Good Labels: On the Self-supervised Labeling for Time Series Forecasting
Yuxuan Yang, Dalin Zhang, Yuxuan Liang et al.
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar et al.
Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady
PathVQ: Reforming Computational Pathology Foundation Model for Whole Slide Image Analysis via Vector Quantization
Honglin Li, Zhongyi Shui, Yunlong Zhang et al.
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Satoki Ishikawa, Makoto Yamada, Han Bao et al.
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
Ruiqi Ni, zherong pan, Ahmed Hussain Qureshi
Point-MaDi: Masked Autoencoding with Diffusion for Point Cloud Pre-training
Xiaoyang Xiao, Runzhao Yao, Zhiqiang Tian et al.