4 papers
Image Translation with Kernel Prediction Networks for Semantic Segmentation
Cristina Mata, Michael S. Ryoo, Henrik Turbell
Semantic segmentation relies on many dense pixel-wise annotations to achieve the best performance, but owing to the difficulty of obtaining accurate annotations for real world data…
CoPT: Unsupervised Domain Adaptive Segmentation using Domain-Agnostic Text Embeddings
Cristina Mata, Kanchana Ranasinghe, Michael S. Ryoo
Unsupervised domain adaptation (UDA) involves learning class semantics from labeled data within a source domain that generalize to an unseen target domain. UDA methods are particul…
Pixel Motion as Universal Representation for Robot Control
Kanchana Ranasinghe, Xiang Li, E-Ro Nguyen +3
We present LangToMo, a vision-language-action framework structured as a dual-system architecture that uses pixel motion forecasts as intermediate representations. Our high-level Sy…
LatentCRF: Continuous CRF for Efficient Latent Diffusion
Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit +5
Latent Diffusion Models (LDMs) produce high-quality, photo-realistic images, however, the latency incurred by multiple costly inference iterations can restrict their applicability.…