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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

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Showing 51–100 of 104 papers

TitleStatusHype
Semantic Neighborhoods as Hypergraphs—0
SHEF-Multimodal: Grounding Machine Translation on Images—0
SRIUBC: Simple Similarity Features for Semantic Textual Similarity—0
Synchronized Audio-Visual Frames with Fractional Positional Encoding for Transformers in Video-to-Text Translation—0
Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description—0
Technical Report: Competition Solution For Modelscope-Sora—0
The Role of the Input in Natural Language Video Description—0
Towards Zero-Shot & Explainable Video Description by Reasoning over Graphs of Events in Space and Time—0
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning—0
Vectors of Locally Aggregated Centers for Compact Video Representation—0
VideoA11y: Method and Dataset for Accessible Video Description—0
VideoCLIP-XL: Advancing Long Description Understanding for Video CLIP Models—0
Video Description: A Survey of Methods, Datasets and Evaluation Metrics—0
VideoMCC: a New Benchmark for Video Comprehension—0
Visual-aware Attention Dual-stream Decoder for Video Captioning—0
A Comprehensive Review on Recent Methods and Challenges of Video Description—0
Incorporating Background Knowledge into Video Description Generation—0
Incorporating Global Visual Features into Attention-based Neural Machine Translation.—0
Incorporating Semantic Attention in Video Description Generation—0
Integrating both Visual and Audio Cues for Enhanced Video Caption—0
Interpretable Video Captioning via Trajectory Structured Localization—0
JU\_CSE\_NLP: Multi-grade Classification of Semantic Similarity between Text Pairs—0
Kubrick: Multimodal Agent Collaborations for Synthetic Video Generation—0
LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living—0
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language—0
MSVD-Turkish: A Comprehensive Multimodal Dataset for Integrated Vision and Language Research in Turkish—0
Multi-Layer Content Interaction Through Quaternion Product For Visual Question Answering—0
Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data—0
Multi-modal News Understanding with Professionally Labelled Videos (ReutersViLNews)—0
Multi Sentence Description of Complex Manipulation Action Videos—0
NarrationBot and InfoBot: A Hybrid System for Automated Video Description—0
Natural Language Descriptions of Human Activities Scenes: Corpus Generation and Analysis—0
Neural Headline Generation on Abstract Meaning Representation—0
Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model—0
Probabilistic Soft Logic for Semantic Textual Similarity—0
Improving LSTM-based Video Description with Linguistic Knowledge Mined from TextCode0
SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous DrivingCode0
VizSeq: A Visual Analysis Toolkit for Text Generation TasksCode0
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video FeaturesCode0
Egocentric Video Description based on Temporally-Linked SequencesCode0
Implicit Location-Caption Alignment via Complementary Masking for Weakly-Supervised Dense Video CaptioningCode0
JMI at SemEval 2024 Task 3: Two-step approach for multimodal ECAC using in-context learning with GPT and instruction-tuned Llama modelsCode0
Predicting Visual Features from Text for Image and Video Caption RetrievalCode0
Describing Unseen Videos via Multi-Modal Cooperative Dialog AgentsCode0
Learn to Understand Negation in Video RetrievalCode0
A Mid-level Video Representation based on Binary Descriptors: A Case Study for Pornography DetectionCode0
Memory-augmented Attention Modelling for VideosCode0
TGIF: A New Dataset and Benchmark on Animated GIF DescriptionCode0
MSVD-Indonesian: A Benchmark for Multimodal Video-Text Tasks in IndonesianCode0
Adversarial Inference for Multi-Sentence Video DescriptionCode0
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