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Tip-adapter: Training-free adaption of clip for few-shot classification
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 …
paradigm for learning visual representations using large-scale image-text pairs. It shows …
Instance segmentation in the dark
Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but
their performance significantly deteriorates in extremely low-light environments. In this work …
their performance significantly deteriorates in extremely low-light environments. In this work …
Pe-yolo: Pyramid enhancement network for dark object detection
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 …
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 …
light vision. Prior works create enhanced representations by either correlating visual quality …
Aleth-nerf: Illumination adaptive nerf with concealing field assumption
The standard Neural Radiance Fields (NeRF) paradigm employs a viewer-centered
methodology, entangling the aspects of illumination and material reflectance into emission …
methodology, entangling the aspects of illumination and material reflectance into emission …