3 papers
cs.CV2026
Lessons and Open Questions from a Unified Study of Camera-Trap Species Recognition Over Time
Sooyoung Jeon, Hongjie Tian, Lemeng Wang +7
Camera traps are vital for large-scale biodiversity monitoring, yet accurate automated analysis remains challenging due to diverse deployment environments. While the computer visio…
cs.LG2025
Revisiting semi-supervised learning in the era of foundation models
Ping Zhang, Zheda Mai, Quang-Huy Nguyen +1
Semi-supervised learning (SSL) leverages abundant unlabeled data alongside limited labeled data to enhance learning. As vision foundation models (VFMs) increasingly serve as the ba…
cs.LG2025
Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition
Zheda Mai, Ping Zhang, Cheng-Hao Tu +3
Parameter-efficient fine-tuning (PEFT) has attracted significant attention due to the growth of pre-trained model sizes and the need to fine-tune (FT) them for superior downstream…