most citedLearning Tri-modal Embeddings for Zero-Shot Soundscape Mapping

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2024

PSM: Learning Probabilistic Embeddings for Multi-scale Zero-Shot Soundscape Mapping

Subash Khanal, Eric Xing, Srikumar Sastry +4

A soundscape is defined by the acoustic environment a person perceives at a location. In this work, we propose a framework for mapping soundscapes across the Earth. Since soundscap…

cs.AI2024

GEOBIND: Binding Text, Image, and Audio through Satellite Images

Aayush Dhakal, Subash Khanal, Srikumar Sastry +2

In remote sensing, we are interested in modeling various modalities for some geographic location. Several works have focused on learning the relationship between a location and typ…

cs.CV20241 cited

GeoSynth: Contextually-Aware High-Resolution Satellite Image Synthesis

Srikumar Sastry, Subash Khanal, Aayush Dhakal +1

We present GeoSynth, a model for synthesizing satellite images with global style and image-driven layout control. The global style control is via textual prompts or geographic loca…

cs.CV2023

BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping

Srikumar Sastry, Subash Khanal, Aayush Dhakal +2

We propose a metadata-aware self-supervised learning~(SSL)~framework useful for fine-grained classification and ecological mapping of bird species around the world. Our framework u…

cs.CV20232 cited

Learning Tri-modal Embeddings for Zero-Shot Soundscape Mapping

Subash Khanal, Srikumar Sastry, Aayush Dhakal +1

We focus on the task of soundscape mapping, which involves predicting the most probable sounds that could be perceived at a particular geographic location. We utilise recent state-…