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Inkyu Shin

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 11:22 PM AMS

10

papers

849

total citations

papers (10)

Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision

Two-phase Pseudo Label Densification for Self-training based Domain Adaptation

MM-TTA: Multi-Modal Test-Time Adaptation for 3D Semantic Segmentation

LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation

TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation

UDA-COPE: Unsupervised Domain Adaptation for Category-Level Object Pose Estimation

Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

NEURIPS 2020arXiv

MATE: Masked Autoencoders are Online 3D Test-Time Learners

Deeply Supervised Flow-Based Generative Models

MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark