activity
20242026
most citedImproving the Detection of Small Oriented Objects in Aerial Images

28 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Towards Continual Test-Time Adaptation of Vision-Language Models in Open-Vocabulary Semantic Segmentation

Chandler Timm C. Doloriel, Yunbei Zhang, Sarthak Kumar Maharana +5

Open-vocabulary semantic segmentation (OVSS) relies on vision-language alignment to recognize arbitrary text-defined categories, yet this alignment is fragile under continual test-…

cs.CV2026

Continual Test-Time Adaptation via Entropy Sensitivity-Guidance in Strict Online Setting

Chandler Timm C. Doloriel, Yunbei Zhang, Muhammad Salman Siddiqui +4

Test-time adaptation (TTA) promises robustness under distribution shift by updating a pretrained model on unlabeled test data, but strict online TTA with batch size one and no acce…

cs.CV2025

Family Matters: A Systematic Study of Spatial vs. Frequency Masking for Continual Test-Time Adaptation

Chandler Timm C. Doloriel, Yunbei Zhang, Yeonguk Yu +6

Recent continual test-time adaptation (CTTA) methods adopt masked image modeling to stabilize learning under distribution shift, yet each treats its masking family F as a fixed des…

cs.CV2025

Towards Sustainable Universal Deepfake Detection with Frequency-Domain Masking

Chandler Timm C. Doloriel, Habib Ullah, Kristian Hovde Liland +2

Universal deepfake detection aims to identify AI-generated images across a broad range of generative models, including unseen ones. This requires robust generalization to new and u…

cs.CV2024★ 1 cited

Frequency Masking for Universal Deepfake Detection

Chandler Timm Doloriel, Ngai-Man Cheung

We study universal deepfake detection. Our goal is to detect synthetic images from a range of generative AI approaches, particularly from emerging ones which are unseen during trai…

cs.CV2024★ 28 cited

Improving the Detection of Small Oriented Objects in Aerial Images

Chandler Timm C. Doloriel, Rhandley D. Cajote

Small oriented objects that represent tiny pixel-area in large-scale aerial images are difficult to detect due to their size and orientation. Existing oriented aerial detectors hav…