HyperAI
HyperAI
الرئيسية
المنصة
الوثائق
الأخبار
الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
شروط الخدمة
سياسة الخصوصية
العربية
HyperAI
HyperAI
Toggle Sidebar
البحث في الموقع...
⌘
K
Command Palette
Search for a command to run...
المنصة
الرئيسية
SOTA
الأسئلة والإجابات على الفيديو بدون تدريب مسبق
Zeroshot Video Question Answer On Msrvtt Qa
Zeroshot Video Question Answer On Msrvtt Qa
المقاييس
Accuracy
Confidence Score
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Accuracy
Confidence Score
Paper Title
Flash-VStream
72.4
3.4
Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams
PLLaVA (34B)
68.7
3.6
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
Elysium
67.5
3.2
Elysium: Exploring Object-level Perception in Videos via MLLM
SlowFast-LLaVA-34B
67.4
3.7
SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
Tarsier (34B)
66.4
3.7
Tarsier: Recipes for Training and Evaluating Large Video Description Models
TS-LLaVA-34B
66.2
3.6
TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
LinVT-Qwen2-VL (7B)
66.2
4.0
LinVT: Empower Your Image-level Large Language Model to Understand Videos
PPLLaVA-7B
64.3
3.5
PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
IG-VLM
63.8
3.5
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM
ST-LLM
63.2
3.4
ST-LLM: Large Language Models Are Effective Temporal Learners
CAT-7B
62.1
3.5
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios
VideoGPT+
60.6
3.6
VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding
Vista-LLaMA-7B
60.5
3.3
Vista-LLaMA: Reducing Hallucination in Video Language Models via Equal Distance to Visual Tokens
MiniGPT4-video-7B
59.73
-
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
LLaVA-Mini
59.5
3.6
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Video-LaVIT
59.3
3.3
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
Video-LLaVA-7B
59.2
3.5
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
LLaMA-VID-13B (2 Token)
58.9
3.3
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
LLaMA-VID-7B (2 Token)
57.7
3.2
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
SUM-shot+Vicuna
56.8
-
Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
0 of 30 row(s) selected.
Previous
Next