A simple attention deep learning model to answer questions about a given video with the most relevant video intervals as answers.
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Updated
Jul 6, 2019 - Python
A simple attention deep learning model to answer questions about a given video with the most relevant video intervals as answers.
A simple attention deep learning model to answer questions about a given video with the most relevant video intervals as answers.
PyTorch code for ROLL, a knowledge-based video story question answering model.
ROCK model for Knowledge-Based VQA in Videos
[ICCV 2021] On the hidden treasure of dialog in video question answering
Video as Conditional Graph Hierarchy for Multi-Granular Question Answering (AAAI'22, Oral)
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
DramaQA Starter Code (2021)
[ACL 2020] PyTorch code for TVQA+: Spatio-Temporal Grounding for Video Question Answering
Multi-Scale Progressive Attention Network for Video Question Answering
This repo contains code for Invariant Grounding for Video Question Answering
Video Graph Transformer for Video Question Answering (ECCV'22)
Code for ACL SustaiNLP 2023 paper "Is a Video worth n × n Images? A Highly Efficient Approach to Transformer-based Video Question Answering"
Code for ACL SRW 2023 paepr "Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering"
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video (ICML 2023)
[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.
[NeurIPS 2022] Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
Part of my work for my Bachelor's Thesis Project on Counterfactual Reasoning for Videos.
[ICCV2023] Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer
A PyTorch implementation of VIOLET
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