Socializing the semantic gap: A comparative survey on image tag assignment, refinement, and retrieval
Where previous reviews on content-based image retrieval emphasize what can be seen in
an image to bridge the semantic gap, this survey considers what people tag about an image …
an image to bridge the semantic gap, this survey considers what people tag about an image …
Large-scale visual sentiment ontology and detectors using adjective noun pairs
We address the challenge of sentiment analysis from visual content. In contrast to existing
methods which infer sentiment or emotion directly from visual low-level features, we propose …
methods which infer sentiment or emotion directly from visual low-level features, we propose …
[PDF][PDF] The MediaMill TRECVID 2006 semantic video search engine
In this paper we describe our TRECVID 2005 experiments. The UvA-MediaMill team
participated in four tasks. For the detection of camera work (runid: A CAM) we investigate the …
participated in four tasks. For the detection of camera work (runid: A CAM) we investigate the …
Harvesting visual concepts for image search with complex queries
The use of image reranking to boost retrieval performance has been found to be successful
for simple queries. It is, however, less effective for complex queries due to the widened …
for simple queries. It is, however, less effective for complex queries due to the widened …
Composite concept discovery for zero-shot video event detection
We consider automated detection of events in video without the use of any visual training
examples. A common approach is to represent videos as classification scores obtained from …
examples. A common approach is to represent videos as classification scores obtained from …
Facilitating image search with a scalable and compact semantic mapping
This paper introduces a novel approach to facilitating image search based on a compact
semantic embedding. A novel method is developed to explicitly map concepts and image …
semantic embedding. A novel method is developed to explicitly map concepts and image …
[PDF][PDF] University of Amsterdam and Renmin University at TRECVID 2017: Searching Video, Detecting Events and Describing Video.
In this paper we summarize our TRECVID 2017 [1] video recognition and retrieval
experiments. We participated in three tasks: video search, event detection and video …
experiments. We participated in three tasks: video search, event detection and video …
Extracting semantic knowledge from web context for multimedia IR: a taxonomy, survey and challenges
Since its invention, the Web has evolved into the largest multimedia repository that has ever
existed. This evolution is a direct result of the explosion of user-generated content …
existed. This evolution is a direct result of the explosion of user-generated content …
Hierarchical concept score postprocessing and concept-wise normalization in CNN-based video event recognition
M Soltanian, S Ghaemmaghami - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper is focused on video event recognition based on frame level convolutional neural
network (CNN) descriptors. Using transfer learning, the image trained descriptors are …
network (CNN) descriptors. Using transfer learning, the image trained descriptors are …
Pooling objects for recognizing scenes without examples
In this paper we aim to recognize scenes in images without using any scene images as
training data. Different from attribute based approaches, we do not carefully select the …
training data. Different from attribute based approaches, we do not carefully select the …