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cs.CV2026
Lightweight Low-Light Image Enhancement via Distribution-Normalizing Preprocessing and Depthwise U-Net
Shimon Murai, Teppei Kurita, Ryuta Satoh +1
We present a lightweight two-stage framework for low-light image enhancement (LLIE) that achieves competitive perceptual quality with significantly fewer parameters than existing m…
cs.CV2026
Revisiting Shape from Polarization in the Era of Vision Foundation Models
Chenhao Li, Taishi Ono, Takeshi Uemori +1
We show that, with polarization cues, a lightweight model trained on a small dataset can outperform RGB-only vision foundation models (VFMs) in single-shot object-level surface nor…