27 citations · 48 across the 5 of their papers we have counts for
8 papers · 1 filter
Retrieval Augmented Classification for Long-Tail Visual Recognition
Alexander Long, Wei Yin, Thalaiyasingam Ajanthan +6
We introduce Retrieval Augmented Classification (RAC), a generic approach to augmenting standard image classification pipelines with an explicit retrieval module. RAC consists of a…
DF-VO: What Should Be Learnt for Visual Odometry?
Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian +2
Multi-view geometry-based methods dominate the last few decades in monocular Visual Odometry for their superior performance, while they have been vulnerable to dynamic and low-text…
Non-Parametric Priors For Generative Adversarial Networks
Rajhans Singh, Pavan Turaga, Suren Jayasuriya +2
The advent of generative adversarial networks (GAN) has enabled new capabilities in synthesis, interpolation, and data augmentation heretofore considered very challenging. However,…
Self-supervised Learning for Single View Depth and Surface Normal Estimation
Huangying Zhan, Chamara Saroj Weerasekera, Ravi Garg +1
In this work we present a self-supervised learning framework to simultaneously train two Convolutional Neural Networks (CNNs) to predict depth and surface normals from a single ima…
Single-view Object Shape Reconstruction Using Deep Shape Prior and Silhouette
Kejie Li, Ravi Garg, Ming Cai +1
3D shape reconstruction from a single image is a highly ill-posed problem. Modern deep learning based systems try to solve this problem by learning an end-to-end mapping from image…
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors
Chamara Saroj Weerasekera, Thanuja Dharmasiri, Ravi Garg +2
We present ``just-in-time reconstruction" as real-time image-guided inpainting of a map with arbitrary scale and sparsity to generate a fully dense depth map for the image. In part…