8 papers
TerraDiT-: Unified Spatial Control for Satellite Image Synthesis with Any Geospatial Primitive
Brian Wei, Srikumar Sastry, Daniel Cher +2
Generative models have achieved remarkable progress, yet applying them to satellite imagery remains challenging. Unlike natural imagery, satellite scenes are structured by spatiall…
Tessellating The Earth
Daniel Cher, Hamza Iqbal, Eric Xing +2
Geolocation encoders, which map geographic coordinates to learned representations, are emerging as an effective means of capturing visual and non-visual characteristics from a lati…
Towards Open-World Generation of Stereo Images and Unsupervised Matching
Feng Qiao, Zhexiao Xiong, Eric Xing +1
Stereo images are fundamental to numerous applications, including extended reality (XR) devices, autonomous driving, and robotics. Unfortunately, acquiring high-quality stereo imag…
Global and Local Entailment Learning for Natural World Imagery
Srikumar Sastry, Aayush Dhakal, Eric Xing +2
Learning the hierarchical structure of data in vision-language models is a significant challenge. Previous works have attempted to address this challenge by employing entailment le…
QuARI: Query Adaptive Retrieval Improvement
Eric Xing, Abby Stylianou, Robert Pless +1
Massive-scale pretraining has made vision-language models increasingly popular for image-to-image and text-to-image retrieval across a broad collection of domains. However, these m…
ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval
Eric Xing, Pranavi Kolouju, Robert Pless +2
Composed image retrieval (CIR) is the task of retrieving a target image specified by a query image and a relative text that describes a semantic modification to the query image. Ex…