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Found 6 papers, 0 papers with code
A Fine-Grained Image Description Generation Method Based on Joint Objectives
The goal of fine-grained image description generation techniques is to learn detailed information from images and simulate human-like descriptions that provide coherent and comprehensive textual details about the image content.
Cross-Modality Earth Mover's Distance for Visible Thermal Person Re-Identification
In this manner, the model will focus on reducing the inter-modality discrepancy while paying less attention to intra-identity variations, leading to a more effective modality alignment.
Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model
At the same time, due to the adoption of an individual-based evolution mechanism, the computational cost of the proposed method is independent of the number of decision variables, thus avoiding the problem of exponential growth of the search space.
Re-ranking Person Re-identification with k-reciprocal Encoding
Specifically, given an image, a k-reciprocal feature is calculated by encoding its k-reciprocal nearest neighbors into a single vector, which is used for re-ranking under the Jaccard distance.
Ranked #13 on
Person Re-Identification
on CUHK03
Detecting Ground Control Points via Convolutional Neural Network for Stereo Matching
Secondly, we present a ground control points selection scheme according to the maximum matching confidence of each pixel.
Video (GIF) Sentiment Analysis using Large-Scale Mid-Level Ontology
However, GIF sentiment analysis is quite challenging, not only because it hinges on spatio-temporal visual contentabstraction, but also for the relationship between such abstraction and final sentiment remains unknown. In this paper, we dedicated to find out such relationship. We proposed a SentiPairSequence basedspatiotemporal visual sentiment ontology, which forms the midlevel representations for GIFsentiment.
