23 citations · 31 across the 15 of their papers we have counts for
6 papers · 1 filter
A Partially Supervised Reinforcement Learning Framework for Visual Active Search
Anindya Sarkar, Nathan Jacobs, Yevgeniy Vorobeychik
Visual active search (VAS) has been proposed as a modeling framework in which visual cues are used to guide exploration, with the goal of identifying regions of interest in a large…
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…
Vision-Language Pseudo-Labels for Single-Positive Multi-Label Learning
Xin Xing, Zhexiao Xiong, Abby Stylianou +3
This paper presents a novel approach to Single-Positive Multi-label Learning. In general multi-label learning, a model learns to predict multiple labels or categories for a single…
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-…
StereoFlowGAN: Co-training for Stereo and Flow with Unsupervised Domain Adaptation
Zhexiao Xiong, Feng Qiao, Yu Zhang +1
We introduce a novel training strategy for stereo matching and optical flow estimation that utilizes image-to-image translation between synthetic and real image domains. Our approa…
Fine-Grained Property Value Assessment using Probabilistic Disaggregation
Cohen Archbold, Benjamin Brodie, Aram Ansary Ogholbake +1
The monetary value of a given piece of real estate, a parcel, is often readily available from a geographic information system. However, for many applications, such as insurance and…