https://github.com/PKU-YuanGroup/LLMBind
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
Papers with Code 아카이브
Zero-Shot Video Question Answer
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 17
- 보존된 평가 기록
- 239
This task present the results of Zeroshot Question Answer results on TGIF-QA dataset for LLM powered Video Conversational Models.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PKU-YuanGroup/MoE-LLaVA
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/QwenLM/Qwen2.5-Omni
https://github.com/ahjeongseo/MASN-pytorch
TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering
https://github.com/baichuan-inc/Baichuan-Omni-1.5
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
https://github.com/chaitanyadwivedii/3D-Attention-is-All-You-Need
TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering
https://github.com/damo-nlp-sg/inf-clip
VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
https://github.com/damo-nlp-sg/videollama3
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
https://github.com/dinhvietcuong1996/icme25-inova
LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
https://github.com/dlvuldet/primevul
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
https://github.com/doc-doc/NExT-OE
https://github.com/facebookresearch/fairseq2
https://github.com/happen2me/cross-gnn
https://github.com/juruobenruo/DexVLA
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
https://github.com/jy0205/lavit
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
https://github.com/jzhang38/EasyContext
https://github.com/klauscc/dam
Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
https://github.com/knowlab/bi-weekly-paper-presentation
https://github.com/lastmile-ai/aiconfig
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
https://github.com/lntzm/cvpr24track-longvideo
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
https://github.com/lucidrains/flamingo-pytorch
https://github.com/mgmalek/efficient_cross_entropy
https://github.com/mlfoundations/open_flamingo
https://github.com/ninglab/ecellm
https://github.com/openbmb/minicpm-v
https://github.com/opengvlab/llama-adapter
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
https://github.com/pku-yuangroup/languagebind
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/pku-yuangroup/video-bench
https://github.com/pwc-1/Paper-9/tree/main/2/minigpt4
https://github.com/pwc-1/Paper-9/tree/main/2/mistral
https://github.com/pwc-1/Paper-9/tree/main/llava_next
LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
https://github.com/qiujihao19/artemis
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
https://github.com/qq326823564/LSDNN
MVB: A Large-Scale Dataset for Baggage Re-Identification and Merged Siamese Networks
https://github.com/qwenlm/qwen2.5-vl
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
https://github.com/skyworkai/moe-plus-plus
https://github.com/skyworkai/moh
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.