33 citations · 33 across the 4 of their papers we have counts for
5 papers · 1 filter
Benchmarking Object Detectors with COCO: A New Path Forward
Shweta Singh, Aayan Yadav, Jitesh Jain +3
The Common Objects in Context (COCO) dataset has been instrumental in benchmarking object detectors over the past decade. Like every dataset, COCO contains subtle errors and imperf…
Hyperbolic Image-Text Representations
Karan Desai, Maximilian Nickel, Tanmay Rajpurohit +2
Visual and linguistic concepts naturally organize themselves in a hierarchy, where a textual concept "dog" entails all images that contain dogs. Despite being intuitive, current la…
Learning Visual Representations via Language-Guided Sampling
Mohamed El Banani, Karan Desai, Justin Johnson
Although an object may appear in numerous contexts, we often describe it in a limited number of ways. Language allows us to abstract away visual variation to represent and communic…
CASTing Your Model: Learning to Localize Improves Self-Supervised Representations
Ramprasaath R. Selvaraju, Karan Desai, Justin Johnson +1
Recent advances in self-supervised learning (SSL) have largely closed the gap with supervised ImageNet pretraining. Despite their success these methods have been primarily applied…
nocaps: novel object captioning at scale
Harsh Agrawal, Karan Desai, Yufei Wang +7
Image captioning models have achieved impressive results on datasets containing limited visual concepts and large amounts of paired image-caption training data. However, if these m…