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Generative Visual Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Generating answers in free form to questions posed about images.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
Towards Flexible Evaluation for Generative Visual Question Answering
SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering
VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
ST-LLM: Large Language Models Are Effective Temporal Learners
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM
LITA: Language Instructed Temporal-Localization Assistant
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios
Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback
Can Generative AI Support Patients' & Caregivers' Informational Needs? Towards Task-Centric Evaluation Of AI Systems
VTimeLLM: Empower LLM to Grasp Video Moments
MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
Generative Visual Question Answering
Multimodal Prompt Retrieval for Generative Visual Question Answering
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
VideoChat: Chat-Centric Video Understanding
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
Flamingo: a Visual Language Model for Few-Shot Learning
PLLay: Efficient Topological Layer based on Persistence Landscapes
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