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SOTA
Zeroshot Video Question Answer
Zeroshot Video Question Answer On Activitynet
Zeroshot Video Question Answer On Activitynet
평가 지표
Accuracy
Confidence Score
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Accuracy
Confidence Score
Paper Title
Repository
MovieChat
45.7
3.1
MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
BT-Adapter (zero-shot)
46.1
3.2
BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
Tarsier (34B)
61.6
3.7
Tarsier: Recipes for Training and Evaluating Large Video Description Models
VideoChat2
49.1
3.3
MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
Chat-UniVi
46.1
3.3
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
LLaMA-VID-13B (2 Token)
47.5
3.3
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
PLLaVA (34B)
60.9
3.7
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
IG-VLM
58.4
3.5
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM
SlowFast-LLaVA-34B
59.2
3.5
SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
LLaVA-Mini
53.5
3.5
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
-
FrozenBiLM
24.7
-
Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
Video Chat
26.5
2.2
VideoChat: Chat-Centric Video Understanding
LLaMA-VID-7B (2 Token)
47.4
3.3
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
Video-ChatGPT
35.2
2.7
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Flash-VStream
51.9
3.4
Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams
Video-LLaVA
45.3
3.3
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
TS-LLaVA-34B
58.9
3.5
TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
Elysium
43.4
2.9
Elysium: Exploring Object-level Perception in Videos via MLLM
PPLLaVA-7B
60.7
3.6
PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
-
LinVT-Qwen2-VL(7B)
60.1
3.6
LinVT: Empower Your Image-level Large Language Model to Understand Videos
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