3 papers
cs.CV2025
Midway Network: Learning Representations for Recognition and Motion from Latent Dynamics
Christopher Hoang, Mengye Ren
Object recognition and motion understanding are key components of perception that complement each other. While self-supervised learning methods have shown promise in their ability…
cs.CV2025
Discrete JEPA: Learning Discrete Token Representations without Reconstruction
Junyeob Baek, Hosung Lee, Christopher Hoang +2
The cornerstone of cognitive intelligence lies in extracting hidden patterns from observations and leveraging these principles to systematically predict future outcomes. However, c…
cs.CV2025
PooDLe: Pooled and dense self-supervised learning from naturalistic videos
Alex N. Wang, Christopher Hoang, Yuwen Xiong +2
Self-supervised learning has driven significant progress in learning from single-subject, iconic images. However, there are still unanswered questions about the use of minimally-cu…