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Video Description

The goal of automatic Video Description is to tell a story about events happening in a video. While early Video Description methods produced captions for short clips that were manually segmented to contain a single event of interest, more recently dense video captioning has been proposed to both segment distinct events in time and describe them in a series of coherent sentences. This problem is a generalization of dense image region captioning and has many practical applications, such as generating textual summaries for the visually impaired, or detecting and describing important events in surveillance footage.

Source: Joint Event Detection and Description in Continuous Video Streams

Papers

Showing 76100 of 104 papers

TitleStatusHype
Egocentric Video Description based on Temporally-Linked SequencesCode0
Attention-Based Multimodal Fusion for Video Description0
Generating Video Description using Sequence-to-sequence Model with Temporal Attention0
Hierarchical Boundary-Aware Neural Encoder for Video Captioning0
Memory-augmented Attention Modelling for VideosCode0
Neural Headline Generation on Abstract Meaning Representation0
Natural Language Descriptions of Human Activities Scenes: Corpus Generation and Analysis0
SHEF-Multimodal: Grounding Machine Translation on Images0
VideoMCC: a New Benchmark for Video Comprehension0
Bidirectional Long-Short Term Memory for Video Description0
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language0
Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model0
A Mid-level Video Representation based on Binary Descriptors: A Case Study for Pornography DetectionCode0
Video Description using Bidirectional Recurrent Neural NetworksCode0
TGIF: A New Dataset and Benchmark on Animated GIF DescriptionCode0
Improving LSTM-based Video Description with Linguistic Knowledge Mined from TextCode0
Vectors of Locally Aggregated Centers for Compact Video Representation0
A Multi-scale Multiple Instance Video Description Network0
Using Descriptive Video Services to Create a Large Data Source for Video Annotation ResearchCode1
Describing Videos by Exploiting Temporal StructureCode0
Probabilistic Soft Logic for Semantic Textual Similarity0
Coherent Multi-Sentence Video Description with Variable Level of Detail0
Semantic Neighborhoods as Hypergraphs0
HENRY-CORE: Domain Adaptation and Stacking for Text Similarity0
Better Exploiting Motion for Better Action Recognition0
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