32 citations · 72 across the 9 of their papers we have counts for
21 papers
Activation Regression for Continuous Domain Generalization with Applications to Crop Classification
Samar Khanna, Bram Wallace, Kavita Bala +1
Geographic variance in satellite imagery impacts the ability of machine learning models to generalise to new regions. In this paper, we model geographic generalisation in medium re…
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Katie Luo, Guandao Yang, Wenqi Xian +3
In applications such as optical see-through and projector augmented reality, producing images amounts to solving non-negative image generation, where one can only add light to an e…
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering
Jang Hyun Cho, Utkarsh Mall, Kavita Bala +1
We present a new framework for semantic segmentation without annotations via clustering. Off-the-shelf clustering methods are limited to curated, single-label, and object-centric i…
Few-Shot Classification with Feature Map Reconstruction Networks
Davis Wertheimer, Luming Tang, Bharath Hariharan
In this paper we reformulate few-shot classification as a reconstruction problem in latent space. The ability of the network to reconstruct a query feature map from support feature…
Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation
Davis Wertheimer, Omid Poursaeed, Bharath Hariharan
We aim to build image generation models that generalize to new domains from few examples. To this end, we first investigate the generalization properties of classic image generator…
Self-training for Few-shot Transfer Across Extreme Task Differences
Cheng Perng Phoo, Bharath Hariharan
Most few-shot learning techniques are pre-trained on a large, labeled "base dataset". In problem domains where such large labeled datasets are not available for pre-training (e.g.,…