103 citations · 109 across the 9 of their papers we have counts for
6 papers · 1 filter
Scaling Data Generation in Vision-and-Language Navigation
Zun Wang, Jialu Li, Yicong Hong +6
Recent research in language-guided visual navigation has demonstrated a significant demand for the diversity of traversable environments and the quantity of supervision for trainin…
Learning Navigational Visual Representations with Semantic Map Supervision
Yicong Hong, Yang Zhou, Ruiyi Zhang +4
Being able to perceive the semantics and the spatial structure of the environment is essential for visual navigation of a household robot. However, most existing works only employ…
PMaF: Deep Declarative Layers for Principal Matrix Features
Zhiwei Xu, Hao Wang, Yanbin Liu +1
We explore two differentiable deep declarative layers, namely least squares on sphere (LESS) and implicit eigen decomposition (IED), for learning the principal matrix features (PMa…
Towards Understanding Gradient Approximation in Equality Constrained Deep Declarative Networks
Stephen Gould, Ming Xu, Zhiwei Xu +1
We explore conditions for when the gradient of a deep declarative node can be approximated by ignoring constraint terms and still result in a descent direction for the global loss…
Adaptive Cross Batch Normalization for Metric Learning
Thalaiyasingam Ajanthan, Matt Ma, Anton van den Hengel +1
Metric learning is a fundamental problem in computer vision whereby a model is trained to learn a semantically useful embedding space via ranking losses. Traditionally, the effecti…
Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths
Ming Xu, Sourav Garg, Michael Milford +1
This paper addresses learning end-to-end models for time series data that include a temporal alignment step via dynamic time warping (DTW). Existing approaches to differentiable DT…