Tip-adapter: Training-free adaption of clip for few-shot classification

R Zhang, W Zhang, R Fang, P Gao, K Li, J Dai… - European conference on …, 2022 - Springer
Abstract Contrastive Vision-Language Pre-training, known as CLIP, has provided a new
paradigm for learning visual representations using large-scale image-text pairs. It shows …

Instance segmentation in the dark

L Chen, Y Fu, K Wei, D Zheng, F Heide - International Journal of Computer …, 2023 - Springer
Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but
their performance significantly deteriorates in extremely low-light environments. In this work …

Pe-yolo: Pyramid enhancement network for dark object detection

X Yin, Z Yu, Z Fei, W Lv, X Gao - International conference on artificial …, 2023 - Springer
Current object detection models have achieved good results on many benchmark datasets,
detecting objects in dark conditions remains a large challenge. To address this issue, we …

Featenhancer: Enhancing hierarchical features for object detection and beyond under low-light vision

KA Hashmi, G Kallempudi… - Proceedings of the …, 2023 - openaccess.thecvf.com
Extracting useful visual cues for the downstream tasks is especially challenging under low-
light vision. Prior works create enhanced representations by either correlating visual quality …

Aleth-nerf: Illumination adaptive nerf with concealing field assumption

Z Cui, L Gu, X Sun, X Ma, Y Qiao… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
The standard Neural Radiance Fields (NeRF) paradigm employs a viewer-centered
methodology, entangling the aspects of illumination and material reflectance into emission …