3 citations · 8 across the 15 of their papers we have counts for
16 papers
TerraDiT: Point-Conditioned Diffusion Transformer for Satellite Image Synthesis
Srikumar Sastry, Dan Cher, Brian Wei +4
We introduce TerraDiT, a diffusion transformer designed for text-to-satellite image generation with point-based control. Existing controlled satellite image generative models often…
SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images
Aayush Dhakal, Subash Khanal, Srikumar Sastry +4
The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state…
ProM3E: Probabilistic Masked MultiModal Embedding Model for Ecology
Srikumar Sastry, Subash Khanal, Aayush Dhakal +4
We introduce ProM3E, a probabilistic masked multimodal embedding model for any-to-any generation of multimodal representations for ecology. ProM3E is based on masked modality recon…
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…
Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping
Subash Khanal, Srikumar Sastry, Aayush Dhakal +3
We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of sounds across the Earth's surface. Exi…
RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings
Aayush Dhakal, Srikumar Sastry, Subash Khanal +3
The choice of representation for geographic location significantly impacts the accuracy of models for a broad range of geospatial tasks, including fine-grained species classificati…
TaxaBind: A Unified Embedding Space for Ecological Applications
Srikumar Sastry, Subash Khanal, Aayush Dhakal +2
We present TaxaBind, a unified embedding space for characterizing any species of interest. TaxaBind is a multimodal embedding space across six modalities: ground-level images of sp…
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…
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…
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…
Eroding Trust In Aerial Imagery: Comprehensive Analysis and Evaluation Of Adversarial Attacks In Geospatial Systems
Michael Lanier, Aayush Dhakal, Zhexiao Xiong +3
In critical operations where aerial imagery plays an essential role, the integrity and trustworthiness of data are paramount. The emergence of adversarial attacks, particularly tho…
LD-SDM: Language-Driven Hierarchical Species Distribution Modeling
Srikumar Sastry, Xin Xing, Aayush Dhakal +3
We focus on species distribution modeling using global-scale presence-only data, leveraging geographical and environmental features to map species ranges, as in previous studies. H…
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…
FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning
Oscar Skean, Aayush Dhakal, Nathan Jacobs +1
Self-supervised learning (SSL) is a popular paradigm for representation learning. Recent multiview methods can be classified as sample-contrastive, dimension-contrastive, or asymme…
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-…
Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images
Aayush Dhakal, Adeel Ahmad, Subash Khanal +3
We propose a weakly supervised approach for creating maps using free-form textual descriptions. We refer to this work of creating textual maps as zero-shot mapping. Prior works hav…