There are 7 repositories under video-question-answering topic.
[CVPR2024 Highlight][VideoChatGPT] ChatGPT with video understanding! And many more supported LMs such as miniGPT4, StableLM, and MOSS.
[ECCV2024] Video Foundation Models & Data for Multimodal Understanding
[CVPR 2021 Best Student Paper Honorable Mention, Oral] Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks.
Official code for MiniGPT4-video
Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Pre-training Dataset and Benchmarks
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video (ICML 2023)
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
[NeurIPS 2022] Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
A PyTorch implementation of VIOLET
[ACL 2020] PyTorch code for TVQA+: Spatio-Temporal Grounding for Video Question Answering
[ICCV 2021 Oral + TPAMI] Just Ask: Learning to Answer Questions from Millions of Narrated Videos
[NeurIPS 2022 Spotlight] Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
[CVPR 2023 Highlight] Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning
A new multi-shot video understanding benchmark Shot2Story with comprehensive video summaries and detailed shot-level captions.
Large Language Models are Temporal and Causal Reasoners for Video Question Answering (EMNLP 2023)
[CVPR 2022] A large-scale public benchmark dataset for video question-answering, especially about evidence and commonsense reasoning. The code used in our paper "From Representation to Reasoning: Towards both Evidence and Commonsense Reasoning for Video Question-Answering", CVPR2022.
[TIP 2022] Official code of paper “Video Question Answering with Prior Knowledge and Object-sensitive Learning”
A PyTorch implementation of EmpiricalMVM
Can I Trust Your Answer? Visually Grounded Video Question Answering (CVPR'24, Highlight)
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models (CVPR 2023)
ROCK model for Knowledge-Based VQA in Videos
Video as Conditional Graph Hierarchy for Multi-Granular Question Answering (AAAI'22, Oral)
[ICCV2023] Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer
PyTorch code for ROLL, a knowledge-based video story question answering model.
Open-Vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models (ICCV 2023)
DramaQA Starter Code (2021)
[NAACL 2024] Official Implementation of paper "Self-Adaptive Sampling for Efficient Video Question Answering on Image--Text Models"
A simple attention deep learning model to answer questions about a given video with the most relevant video intervals as answers.
LifeQA website code
Code for ACL SRW 2023 paepr "Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering"