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Found 9 papers, 2 papers with code
Biomedical Concept Normalization by Leveraging Hypernyms
Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module.
Feature Prediction Diffusion Model for Video Anomaly Detection
Motivated by the impressive generative and anti-noise capacity of diffusion model (DM), in this work, we introduce a novel DM-based method to predict the features of video frames for anomaly detection.
Ranked #8 on
Anomaly Detection
on UBnormal
Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection
As a by-product, a CapS dataset is constructed by augmenting existing benchmark training set with additional image tags and captions.
BV-Person: A Large-Scale Dataset for Bird-View Person Re-Identification
In this work we introduce a new ReID task, bird-view person ReID, which aims at searching for a person in a gallery of horizontal-view images with the query images taken from a bird's-eye view, i. e., an elevated view of an object from above.
Occluded Person Re-Identification With Single-Scale Global Representations
However, real-world ReID applications typically have highly diverse occlusions and involve a hybrid of occluded and non-occluded pedestrians.
A New Action Recognition Framework for Video Highlights Summarization in Sporting Events
To date, machine learning for human action recognition in video has been widely implemented in sports activities.
Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss
The proposed loss is generic and can be used as a plugin to replace the triplet loss to significantly enhance different types of state-of-the-art approaches.
Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection
Video anomaly detection is of critical practical importance to a variety of real applications because it allows human attention to be focused on events that are likely to be of interest, in spite of an otherwise overwhelming volume of video.
Unified Multifaceted Feature Learning for Person Re-Identification
The loss structures the augmented images resulted by the two types of image erasing in a two-level hierarchy and enforces multifaceted attention to different parts.
