I’m giving a talk on this at #VSS2026: Sun May 17, 8:30am, Talk Room 2 (Object Recognition, 31.22). My first VSS! www.visionsciences.org/talk-session...
Thanks to coauthors @tarunsepuri.bsky.social @alvinwmtan.bsky.social, @khaiaw.bsky.social, @mcxfrank.bsky.social, and @brialong.bsky.social!
Content: huge variation in viewpoint & format — including lots of depictions (esp. animals—examples below!!.
Children are learning about many categories from these kinds of “child-directed” visuals rather than real-life exemplars.
Category organization: We found stronger within-superordinate clustering in the child’s view than in a curated dataset (THINGS). We also find this pattern in data from individual children.
Maybe this provides a way for children to parse the “blooming buzzing confusion” of their visual world!
Children acquire object category representations from their everyday experiences in the first few years of life.
What do the inputs to this learning process actually look like?
New preprint! arxiv.org/abs/2605.14990
We analyzed the objects in view in 868 hours of egocentric videos from the BabyView dataset—from 31 children (5-36 months old). We used an object detection model to extract object categories from >3M frames—pipeline below.
And more about the BabyView Project here! babyview-project.github.io
Children acquire object category representations from their everyday experiences in the first few years of life. What do the inputs to this learning process look like? We analyzed first-person videos ...
arxiv.org
jane-yang.bsky.social
jane-yang.bsky.social
jane-yang.bsky.social
jane-yang.bsky.social
jane-yang.bsky.social
What did we find? First, we found that a few categories dominate — across all domains! Children see some categories much more often than others, replicating prior work.
