https://github.com/antoyang/FrozenBiLM
공식 코드Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
Papers with Code 아카이브
Video Question Answering
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/antoyang/just-ask
공식 코드Just Ask: Learning to Answer Questions from Millions of Narrated Videos
https://github.com/apple/ml-slowfast-llava
공식 코드SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
https://github.com/aurooj/shg-vqa
공식 코드Learning Situation Hyper-Graphs for Video Question Answering
https://github.com/baaivision/emu
공식 코드https://github.com/bcmi/causal-vidqa
공식 코드https://github.com/becomebright/groundvqa
공식 코드https://github.com/becomebright/rekv
공식 코드Streaming Video Question-Answering with In-context Video KV-Cache Retrieval
https://github.com/bigai-nlco/lstp-chat
공식 코드Efficient Temporal Extrapolation of Multimodal Large Language Models with Temporal Grounding Bridge
https://github.com/bigai-nlco/videotgb
공식 코드Efficient Temporal Extrapolation of Multimodal Large Language Models with Temporal Grounding Bridge
https://github.com/boheumd/MA-LMM
공식 코드MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding
https://github.com/briansidp/audiovisualllm
공식 코드Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models
https://github.com/brown-palm/Vamos
공식 코드https://github.com/bytedance/Shot2Story
공식 코드Shot2Story20K: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
https://github.com/bytedance/tarsier
공식 코드https://github.com/bytedance/video-salmonn-2
공식 코드video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language Models
https://github.com/byz0e/glance-focus
공식 코드Glance and Focus: Memory Prompting for Multi-Event Video Question Answering
https://github.com/caicch/colpro
공식 코드Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting
https://github.com/ceezh/llovi
공식 코드A Simple LLM Framework for Long-Range Video Question-Answering
https://github.com/computer-vision-in-the-wild/cvinw_readings
공식 코드Vision-Language Pre-training: Basics, Recent Advances, and Future Trends
https://github.com/contrastive/freevideollm
공식 코드Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs
https://github.com/cuthbertcai/demovlp
공식 코드Revitalize Region Feature for Democratizing Video-Language Pre-training of Retrieval
https://github.com/cvlab-columbia/viper
공식 코드ViperGPT: Visual Inference via Python Execution for Reasoning
https://github.com/damo-nlp-sg/video-llama
공식 코드Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
https://github.com/damo-nlp-sg/videollama2
공식 코드VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
https://github.com/damo-nlp-sg/videollama3
공식 코드VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
https://github.com/daromog/q-vid
공식 코드Question-Instructed Visual Descriptions for Zero-Shot Video Question Answering
https://github.com/declare-lab/sas-vqa
공식 코드Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models
https://github.com/declare-lab/sealing
공식 코드Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models
https://github.com/deep-spin/infinite-video
공식 코드https://github.com/deepmind/perception_test
공식 코드Perception Test: A Diagnostic Benchmark for Multimodal Video Models
https://github.com/doc-doc/NExT-QA
공식 코드NExT-QA:Next Phase of Question-Answering to Explaining Temporal Actions
https://github.com/doc-doc/covgt
공식 코드Contrastive Video Question Answering via Video Graph Transformer
https://github.com/doc-doc/hqga
공식 코드Video as Conditional Graph Hierarchy for Multi-Granular Question Answering
https://github.com/doc-doc/next-gqa
공식 코드Can I Trust Your Answer? Visually Grounded Video Question Answering
https://github.com/doc-doc/vRGV
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.