2 papers
cs.CV2026
CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment
Chongyi Li, Chunle Guo, Ruicheng Feng +2
We present Curve Distillation, CuDi, for efficient and controllable exposure adjustment without the requirement of paired or unpaired data during training. Our method inherits the…
cs.CV2024
MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation
Jiahao Xie, Wei Li, Xiangtai Li +3
We present MosaicFusion, a simple yet effective diffusion-based data augmentation approach for large vocabulary instance segmentation. Our method is training-free and does not rely…