Showing cs.CVShow all
3 papers · 1 filter
cs.CV2023
Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection
Kwangrok Ryoo, Yeonsik Jo, Seungjun Lee +5
For object detection task with noisy labels, it is important to consider not only categorization noise, as in image classification, but also localization noise, missing annotations…
cs.CV2023
Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pretraining
Bumsoo Kim, Yeonsik Jo, Jinhyung Kim +1
Contrastive Language-Image Pretraining has emerged as a prominent approach for training vision and text encoders with uncurated image-text pairs from the web. To enhance data-effic…
cs.CV2023
Expediting Contrastive Language-Image Pretraining via Self-distilled Encoders
Bumsoo Kim, Jinhyung Kim, Yeonsik Jo +1
Recent advances in vision language pretraining (VLP) have been largely attributed to the large-scale data collected from the web. However, uncurated dataset contains weakly correla…