Self-Supervised Vision Transformers

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PolSAR Image Classification using a Hybrid Complex-Valued Network (HybridCVNet)
May 29, 2026Mohammed Q. AlkhatibHyperspectral Image Classification Synthetic Aperture Radar
QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer
May 29, 2026Zhizhen Pan, Hesong Wang, Huan Wang3D Perception Self-Supervised Vision Transformers
Polyphony: Diffusion-based Dual-Hand Action Segmentation with Alternating Vision Transformer and Semantic Conditioning
May 29, 2026Hao Zheng, Hu Wang, Tiantian Zheng +2Temporal Action Segmentation Bimanual Manipulation
Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
May 28, 2026Fanny Lehmann, Firat Ozdemir, Yun Cheng +4Artificial Intelligence Weather Models Long-Horizon Forecasting
SwInception -- Local Attention Meets Convolutions
May 28, 2026David Hagerman, Roman Naeem, Jakob Lindqvist +3Swin Self-Supervised Vision Transformers
SlideCheck: Guiding Self-Supervised Pretraining of Pathology Foundation Models via Dataset Distributions
May 28, 2026Mingyi He, Xinyi Guo, Xitong Ling +7Pathology Foundation Models Pathology
Parameter-Efficient Subspace Decoupling ViT for Mitigating Multi-Task Negative Transfer in Histological Scoring
May 28, 2026Youhan Huang, Jiajun Li, Yilin Fang +2Multi--Task Learning Self-Supervised Vision Transformers
Low-Magnification SEM May Suffice: Interpretable Deep Learning for Multi-Scale Fracture-Cause Classification in Zirconia-Toughened Alumina
May 28, 2026Julian Schmid, Pawel Astankow, Tom Vater +3Transmission Electron Microscopy Scalable Defect Detection
Accelerating HEVC Intra Partitioning via a CNN-Hierarchical Attention Transformer Hybrid
May 27, 2026Krishna Kumar Sharma, Somdyuti PaulSelf-Supervised Vision Transformers Neural Video Codecs
Recursive Vision Transformer with Dynamic Depth and Width Adjustment for Resource-Efficient Image Semantic Communication
May 27, 2026Zhilong Zhang, Xinhui Zhang, Gongyu Jin +3Self-Supervised Vision Transformers Vision Transformer
JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search
May 26, 2026Dongyun Zou, Zhuoyang Zhang, Junyu Chen +8Self-Supervised Vision Transformers Vision Foundation Models
CSV-ViT: A Vision Transformer with the Variable-sized Cortical Supervertices for Detection of Alzheimer's Disease Pathologies
May 26, 2026Geonwoo Baek, Ikbeom JangAlzheimer Self-Supervised Vision Transformers
ATV-Net: Adaptive Triple-View Network with Dynamic Feature Fusion
May 25, 2026Sheng-Wei Chan, Hsin-Jui Pan, Chun-Po Shen +3Dense Semantic Segmentation Self-Supervised Vision Transformers
X-Edit: Exact, Explicit, and Explainable Null-Space Editing for Medical Vision Transformers
May 24, 2026Yuanye Liu, Siyuan Zhou, Ke Zhang +3Self-Supervised Vision Transformers Medical Vision-Language Models
Good Token Hunting: A Hitchhiker's Guide to Token Selection for Visual Geometry Transformers
May 22, 2026Shuhong Zheng, Michael Oechsle, Erik Sandström +3Self-Supervised Vision Transformers 3D Scene Understanding
Improved Vision-to-Chart Buoy Association with Learned World-to-Image Projection
May 21, 2026Borja Carrillo-PerezSelf-Supervised Vision Transformers Pixels
ORBIS: Output-Guided Token Reduction with Distribution-Aware Matching for Video Diffusion Acceleration
May 21, 2026Hangyeol Lee, Joo-Young KimPre-Trained Video Diffusion Models Self-Supervised Vision Transformers
Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness
May 21, 2026Hangyeol Lee, Hyojeong Lee, Joo-Young KimMultimodal Diffusion Transformers Self-Supervised Vision Transformers
Deformba: Vision State Space Model with Adaptive State Fusion
May 20, 2026Hongyu Ke, Jack Morris, Yongkang Liu +4Self-Supervised Vision Transformers Progressive Attention Fusion
FTerViT: Fully Ternary Vision Transformer
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LiteViLNet: Lightweight Vision-LiDAR Fusion Network for Efficient Road Segmentation
May 20, 2026Daojie Peng, Bingtao Wang, Fulong Ma +2Dense Semantic Segmentation Lidar
UniRefiner: Teaching Pre-trained ViTs to Self-Dispose Dross via Contrastive Register
May 19, 2026Congpei Qiu, Zhaoyu Hu, Wei Ke +3Self-Supervised Vision Transformers Vision Transformer
Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling
May 18, 2026Yihang Wu, Yihang Sun, Shaofeng Zhang +4Novel View Synthesis Self-Supervised Vision Transformers
LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift
May 18, 2026Haozhe Si, Yuxuan Wan, Yuqing Wang +2Hyperspectral Imaging Self-Supervised Vision Transformers
Token-Space Mask Prediction for Efficient Vision Transformer Segmentation
May 18, 2026Calvin Galagain, Martyna Poreba, François GouletteSelf-Supervised Vision Transformers Convolutional Neural Networks
Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction
May 18, 2026Yu Li, Puchao Zhou, Yachun Mi +3Image Quality Assessment Self-Supervised Vision Transformers
VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment
May 16, 2026Amy Makawana, Abhijeet Parida, Marius George Linguraru +2Brain Magnetic Resonance Imaging 3D Semantic Segmentation
Registers Matter for Pixel-Space Diffusion Transformers
May 15, 2026Nikita Starodubcev, Ilia Sudakov, Ilya Drobyshevskiy +2Multimodal Diffusion Transformers Self-Supervised Vision Transformers
SCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation
May 14, 2026Hanxu Zhang, Chen Jia, Hui Liu +3Self-Supervised Vision Transformers
Representative Attention For Vision Transformers
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Hierarchical Image Tokenization for Multi-Scale Image Super Resolution
May 14, 2026Isma Hadji, Enrique Sanchez, Adrian Bulat +2Self-Supervised Vision Transformers Visual Autoregressive Models
SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection
May 13, 2026Sandro Papais, Lezhou Feng, Charles Cossette +13D Object Detection 3D Object Understanding
Elastic Attention Cores for Scalable Vision Transformers
May 12, 2026Alan Z. Song, Yinjie Chen, Mu Nan +8Self-Supervised Vision Transformers Vision Transformer
AOI-SSL: Self-Supervised Framework for Efficient Segmentation of Wire-bonded Semiconductors In Optical Inspection
May 12, 2026Joaquín Figueira, Rob Van Gastel, Giacomo D'Amicantonio +4Self-Supervised Self-Supervised Vision Transformers
Spectral Vision Transformer for Efficient Tokenization with Limited Data
May 12, 2026Alexandra G. Roberts, Maneesh John, Jinwei Zhang +10Self-Supervised Vision Transformers Vision Transformer
Vision Transformer-Conditioned UNet for Domain-Adaptive Semantic Segmentation
May 12, 2026Joel Valdivia Ortega, Tingying Peng, Marion JasninSelf-Supervised Vision Transformers U-Net
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TCP-SSM: Efficient Vision State Space Models with Token-Conditioned Poles
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bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition
May 11, 2026Michal Byra, Pawel Olszowiec, Grzegorz Stefanski +2Vision Transformer Self-Supervised Vision Transformers
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May 11, 2026Novendra Setyawan, Chi-Chia Sun, Mao-Hsiu Hsu +2Self-Supervised Vision Transformers Vision Transformer
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May 9, 2026Frank Li, Bardia Khosravi, Mohammadreza Chavoshi +5Medical Imaging Multimodal Clinical Data
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Dynamic Mode Decomposition along Depth in Vision Transformers
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Amortized-Precision Quantization for Early-Exit Vision Transformers
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TAS-LoRA: Transformer Architecture Search with Mixture-of-LoRA Experts
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Attention Transfer Is Not Universally Effective for Vision Transformers
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May 7, 2026Frederik Schäfer, Luis Mandl, Lars Kälber +1Noisy Labels Self-Supervised Vision Transformers
MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
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A Robust Foundation Model for Conservation Laws: Injecting Context into Flux Neural Operators via Recurrent Vision Transformers
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VC-FeS: Viewpoint-Conditioned Feature Selection for Vehicle Re-identification in Thermal Vision
May 6, 2026Yasod Ginige, Ransika Gunasekara, Darsha Hewavitharana +3Thermal Imaging Robust Vehicle Recognition
RD-ViT: Recurrent-Depth Vision Transformer for Semantic Segmentation with Reduced Data Dependence Extending the Recurrent-Depth Transformer Architecture to Dense Prediction
May 5, 2026Renjie HeSelf-Supervised Vision Transformers Whole-Heart Segmentation
Neuroscience-Inspired Analyses of Visual Interestingness in Multimodal Transformers
May 5, 2026Mathis Immertreu, Fitim Abdullahu, Thomas Kinfe +3Multimodal Transformers Transformer Attention
Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers
May 5, 2026Lorenzo Mur-Labadia, Ruben Martinez-Cantina, Jose J. GuerreroUncertainty-Aware Inference Affordances
Linearizing Vision Transformer with Test-Time Training
May 4, 2026Yining Li, Dongchen Han, Zeyu Liu +3Self-Supervised Vision Transformers Vision Transformer
AgriKD: Cross-Architecture Knowledge Distillation for Efficient Leaf Disease Classification
May 2, 2026Minh-Dung Le, Minh-Duc Hoang, Hoang-Vu Truong +1Tomato Diseases Apple Tree Leaf Disease Segmentation Dataset
Energy-Efficient Plant Monitoring via Knowledge Distillation
Apr 29, 2026Ilyass Moummad, Reda Bensaid, Kawtar Zaher +5Tomato Diseases Knowledge Distillation
Adaptive Transform Coding for Semantic Compression
Apr 29, 2026Andriy Enttsel, Vincent CorlaySelf-Supervised Vision Transformers Rate-Distortion Theory
Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models
Apr 28, 2026Dewei Bai, Hongxiang Peng, Yunyun Zeng +3Self-Supervised Vision Transformers Visual Token Pruning

May 29, 2026 · cs.CVJ/K move · Enter open · S save

PolSAR Image Classification using a Hybrid Complex-Valued Network (HybridCVNet)

Mohammed Q. Alkhatib

Recently, convolutional neural networks (CNNs) have become popular for image classification due to their effectiveness in computer vision tasks. Now, researchers are exploring the potential of vision transformers (ViTs) in remote sensing and Earth observation. However, traditional Real-Valued networks often overlook important phase information in Complex-Valued (CV) data like polarimetric synthetic aperture radar (PolSAR) data. To address this, new CV deep architectures have emerged. HybridCVNet, a novel hybrid network, blends CV-CNN and CV vision transformer (CV-ViT) techniques. It efficiently combines CV 3D and 2D CNNs as feature extractors, enhancing PolSAR image classification by extracting complementary information and effectively leveraging interdependencies within the data. Experimental results from widely-used PolSAR datasets show HybridCVNet outperforms other methods, achieving an overall accuracy of 97.39% on the Flevoland dataset and showing promise even with just a 1% sampling ratio, with a Kappa value of 0.972 on the San Francisco dataset. Source code is accessible through https://github.com/mqalkhatib/HybridCVNet

Hyperspectral Image Classification Synthetic Aperture Radar Convolutional Neural Networks Image Classification 3D Convolutional Neural Networks Self-Supervised Vision Transformers

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