Highlight Detection
27 papers with code • 3 benchmarks • 2 datasets
Libraries
Use these libraries to find Highlight Detection models and implementationsMost implemented papers
QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
Each video in the dataset is annotated with: (1) a human-written free-form NL query, (2) relevant moments in the video w. r. t.
Correlation-guided Query-Dependency Calibration in Video Representation Learning for Temporal Grounding
Dummy tokens conditioned by text query take portions of the attention weights, preventing irrelevant video clips from being represented by the text query.
AENet: Learning Deep Audio Features for Video Analysis
Instead, combining visual features with our AENet features, which can be computed efficiently on a GPU, leads to significant performance improvements on action recognition and video highlight detection.
Video Highlights Detection and Summarization with Lag-Calibration based on Concept-Emotion Mapping of Crowd-sourced Time-Sync Comments
With the prevalence of video sharing, there are increasing demands for automatic video digestion such as highlight detection.
PHD-GIFs: Personalized Highlight Detection for Automatic GIF Creation
Highlight detection models are typically trained to identify cues that make visual content appealing or interesting for the general public, with the objective of reducing a video to such moments.
Single Image Highlight Removal with a Sparse and Low-Rank Reflection Model
We propose a sparse and low-rank reflection model for specular highlight detection and removal using a single input image.
SoccerDB: A Large-Scale Database for Comprehensive Video Understanding
Soccer videos can serve as a perfect research object for video understanding because soccer games are played under well-defined rules while complex and intriguing enough for researchers to study.
Adaptive Video Highlight Detection by Learning from User History
In this paper, we propose a simple yet effective framework that learns to adapt highlight detection to a user by exploiting the user's history in the form of highlights that the user has previously created.
Learning to Detect Specular Highlights from Real-world Images
Specular highlight detection is a challenging problem, and has many applications such as shiny object detection and light source estimation.
A Multi-Task Network for Joint Specular Highlight Detection and Removal
Specular highlight detection and removal are fundamental and challenging tasks.