28 citations · 63 across the 7 of their papers we have counts for
12 papers · 1 filter
Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach
Zhenyu Wu, Karthik Suresh, Priya Narayanan +3
Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. Despite the great success of the generic object detection methods trained…
Semantics to Space(S2S): Embedding semantics into spatial space for zero-shot verb-object query inferencing
Sungmin Eum, Heesung Kwon
We present a novel deep zero-shot learning (ZSL) model for inferencing human-object-interaction with verb-object (VO) query. While the previous two-stream ZSL approaches only use t…
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification
Colin Samplawski, Heesung Kwon, Erik Learned-Miller +1
Zero-shot learning (ZSL) is one of the most extreme forms of learning from scarce labeled data. It enables predicting that images belong to classes for which no labeled training in…
S-DOD-CNN: Doubly Injecting Spatially-Preserved Object Information for Event Recognition
Hyungtae Lee, Sungmin Eum, Heesung Kwon
We present a novel event recognition approach called Spatially-preserved Doubly-injected Object Detection CNN (S-DOD-CNN), which incorporates the spatially preserved object detecti…
Is Pretraining Necessary for Hyperspectral Image Classification?
Hyungtae Lee, Sungmin Eum, Heesung Kwon
We address two questions for training a convolutional neural network (CNN) for hyperspectral image classification: i) is it possible to build a pre-trained network? and ii) is the…
DOD-CNN: Doubly-injecting Object Information for Event Recognition
Hyungtae Lee, Sungmin Eum, Heesung Kwon
Recognizing an event in an image can be enhanced by detecting relevant objects in two ways: 1) indirectly utilizing object detection information within the unified architecture or…