:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Kazakov, Allan, Cakir, Duygu, İrfanoğlu, Hilal Kurt, İrfanoğlu, Yavuz
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2605.23747
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Vision Transformers: From Semantic Segmentation to Dense Prediction
by: Zhang, Li, et al.
Published: (2022)

Quantization Robustness to Input Degradations for Object Detection
by: Karimov, Toghrul, et al.
Published: (2025)

Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
by: Bai, Jinbin, et al.
Published: (2024)

Dense Vision Transformer Compression with Few Samples
by: Zhang, Hanxiao, et al.
Published: (2024)

RD-ViT: Recurrent-Depth Vision Transformer for Semantic Segmentation with Reduced Data Dependence Extending the Recurrent-Depth Transformer Architecture to Dense Prediction
by: He, Renjie
Published: (2026)

VPNeXt -- Rethinking Dense Decoding for Plain Vision Transformer
by: Tang, Xikai, et al.
Published: (2025)

The Power of Certainty: How Confident Models Lead to Better Segmentation
by: Erol, Tugberk, et al.
Published: (2025)

CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
by: Wu, Size, et al.
Published: (2023)

MaterialSeg3D: Segmenting Dense Materials from 2D Priors for 3D Assets
by: Li, Zeyu, et al.
Published: (2024)

Native Segmentation Vision Transformers
by: Brasó, Guillem, et al.
Published: (2025)

SHED Light on Segmentation for Dense Prediction
by: Lee, Seung Hyun, et al.
Published: (2026)

Revisiting Audio-Visual Segmentation with Vision-Centric Transformer
by: Huang, Shaofei, et al.
Published: (2025)

CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning
by: Mushtaq, Erum, et al.
Published: (2024)

DisentangleFormer: Spatial-Channel Decoupling for Multi-Channel Vision
by: Liao, Jiashu, et al.
Published: (2025)

Virtual Category Learning: A Semi-Supervised Learning Method for Dense Prediction with Extremely Limited Labels
by: Chen, Changrui, et al.
Published: (2023)

ViT-CoMer: Vision Transformer with Convolutional Multi-scale Feature Interaction for Dense Predictions
by: Xia, Chunlong, et al.
Published: (2024)

DenSe-AdViT: A novel Vision Transformer for Dense SAR Object Detection
by: Zhang, Yang, et al.
Published: (2025)

Unified Review and Benchmark of Deep Segmentation Architectures for Cardiac Ultrasound on CAMUS
by: Ullah, Zahid, et al.
Published: (2025)

DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation
by: Hayder, Zeeshan, et al.
Published: (2024)

Weakly Supervised Food Image Segmentation using Vision Transformers and Segment Anything Model
by: Sarafis, Ioannis, et al.
Published: (2025)

Improving Video Diffusion Transformer Training by Multi-Feature Fusion and Alignment from Self-Supervised Vision Encoders
by: Lee, Dohun, et al.
Published: (2025)

SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios
by: Hirano, Shozaburo, et al.
Published: (2026)

Dino-NestedUNet: Unlocking Foundation Vision Encoders for Pathology Tumor Bulk Segmentation via Dense Decoding
by: Wang, Tianyang, et al.
Published: (2026)

Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting System
by: Li, Mingjie, et al.
Published: (2022)

Token-Space Mask Prediction for Efficient Vision Transformer Segmentation
by: Galagain, Calvin, et al.
Published: (2026)

Boundary-Aware Vision Transformer for Angiography Vascular Network Segmentation
by: Hezil, Nabil, et al.
Published: (2025)

Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks
by: Liu, Yuhao, et al.
Published: (2024)

DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling
by: Ai, Yuang, et al.
Published: (2025)

MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
by: Reza, Md Kaykobad, et al.
Published: (2023)

Multi-Layer Dense Attention Decoder for Polyp Segmentation
by: Patel, Krushi, et al.
Published: (2024)

Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network
by: Alkendi, Yusra, et al.
Published: (2024)

Self-Supervised Vision Transformers Are Efficient Segmentation Learners for Imperfect Labels
by: Lee, Seungho, et al.
Published: (2024)

AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets
by: Du, Siyi, et al.
Published: (2023)

Forest2Seq: Revitalizing Order Prior for Sequential Indoor Scene Synthesis
by: Sun, Qi, et al.
Published: (2024)

DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation
by: Keuth, Ron, et al.
Published: (2024)

Representation Separation for Semantic Segmentation with Vision Transformers
by: Hong, Yuanduo, et al.
Published: (2022)

Memory Efficient Transformer Adapter for Dense Predictions
by: Zhang, Dong, et al.
Published: (2025)

DBAT: Dynamic Backward Attention Transformer for Material Segmentation with Cross-Resolution Patches
by: Heng, Yuwen, et al.
Published: (2023)

Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation
by: Stolle, Kurt H. W.
Published: (2024)

DenseGrounding: Improving Dense Language-Vision Semantics for Ego-Centric 3D Visual Grounding
by: Zheng, Henry, et al.
Published: (2025)