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Video Question Answering

Papers

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Showing 51–100 of 460 papers

TitleStatusHype
VidEgoThink: Assessing Egocentric Video Understanding Capabilities for Embodied AICode2
CausalVQA: A Physically Grounded Causal Reasoning Benchmark for Video ModelsCode2
Video-Panda: Parameter-efficient Alignment for Encoder-free Video-Language ModelsCode2
video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language ModelsCode2
Elysium: Exploring Object-level Perception in Videos via MLLMCode2
Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive LearningCode2
All in One: Exploring Unified Video-Language Pre-trainingCode2
vid-TLDR: Training Free Token merging for Light-weight Video TransformerCode2
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame SelectionCode2
VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and DatasetCode2
Video in 10 Bits: Few-Bit VideoQA for Efficiency and PrivacyCode2
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video UnderstandingCode2
TimeSuite: Improving MLLMs for Long Video Understanding via Grounded TuningCode2
Task Me AnythingCode2
VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and DatasetCode2
FreeVA: Offline MLLM as Training-Free Video AssistantCode2
Direct Preference Optimization of Video Large Multimodal Models from Language Model RewardCode2
Streaming Video Question-Answering with In-context Video KV-Cache RetrievalCode2
Revealing Single Frame Bias for Video-and-Language LearningCode2
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMsCode2
LLaMA-VID: An Image is Worth 2 Tokens in Large Language ModelsCode2
ST-LLM: Large Language Models Are Effective Temporal LearnersCode2
Perception Test: A Diagnostic Benchmark for Multimodal Video ModelsCode2
LingoQA: Visual Question Answering for Autonomous DrivingCode2
LinVT: Empower Your Image-level Large Language Model to Understand VideosCode2
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMsCode2
Perception Test: A Diagnostic Benchmark for Multimodal ModelsCode2
PPLLaVA: Varied Video Sequence Understanding With Prompt GuidanceCode2
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular FusionCode2
Online Video Understanding: OVBench and VideoChat-OnlineCode2
MVBench: A Comprehensive Multi-modal Video Understanding BenchmarkCode2
LITA: Language Instructed Temporal-Localization AssistantCode2
COSA: Concatenated Sample Pretrained Vision-Language Foundation ModelCode1
Contrastive Video Question Answering via Video Graph TransformerCode1
A Simple LLM Framework for Long-Range Video Question-AnsweringCode1
Large Language Models are Temporal and Causal Reasoners for Video Question AnsweringCode1
LAVENDER: Unifying Video-Language Understanding as Masked Language ModelingCode1
Connecting Vision and Language with Video Localized NarrativesCode1
Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question AnsweringCode1
Language Models with Image Descriptors are Strong Few-Shot Video-Language LearnersCode1
Just Ask: Learning to Answer Questions from Millions of Narrated VideosCode1
AnyMAL: An Efficient and Scalable Any-Modality Augmented Language ModelCode1
Knowledge-Based Video Question Answering with Unsupervised Scene DescriptionsCode1
Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal ModelingCode1
Invariant Grounding for Video Question AnsweringCode1
MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video Question AnsweringCode1
Clover: Towards A Unified Video-Language Alignment and Fusion ModelCode1
Learning Video Context as Interleaved Multimodal SequencesCode1
-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory ConsolidationCode1
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All datasetsNExT-QAActivityNet-QATVBenchMVBenchMSRVTT-QASTAR BenchmarkOVBenchAGQA 2.0 balancedHow2QAiVQAMSRVTT-MCIntentQA

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LinVT-Qwen2-VL (7B)Accuracy85.5—Unverified
2InternVL-2.5(8B)Accuracy85.5—Unverified
3VideoLLaMA3(7B)Accuracy84.5—Unverified
4PLM-8BAccuracy84.1—Unverified
5BIMBA-LLaVA-Qwen2-7BAccuracy83.73—Unverified
6PLM-3BAccuracy83.4—Unverified
7LLaVA-VideoAccuracy83.2—Unverified
8NVILA(8B)Accuracy82.2—Unverified
9Oryx-1.5(7B)Accuracy81.8—Unverified
10Qwen2-VL(7B)Accuracy81.2—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-2 + CLIP-14 + CLIP-multilingual (Zero-Shot)Accuracy61.2—Unverified
2GPT-2 + CLIP-32 (Zero-Shot)Accuracy58.4—Unverified
3VideoCoCaAccuracy56.1—Unverified
4Mirasol3BAccuracy51.13—Unverified
5VASTAccuracy50.4—Unverified
6COSAAccuracy49.9—Unverified
7MA-LMMAccuracy49.8—Unverified
8VideoChat2Accuracy49.1—Unverified
9VALORAccuracy48.6—Unverified
10UMT-L (ViT-L/16)Accuracy47.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Seed1.5-VL thinkingAverage Accuracy63.6—Unverified
2PLM-8BAverage Accuracy63.5—Unverified
3Seed1.5-VLAverage Accuracy61.5—Unverified
4V-JEPA 2 ViT-g 8BAverage Accuracy60.6—Unverified
5PLM-3BAverage Accuracy58.9—Unverified
6RRPOAverage Accuracy56.5—Unverified
7Tarsier-34BAverage Accuracy55.5—Unverified
8Tarsier2-7BAverage Accuracy54.7—Unverified
9Qwen2-VL-72BAverage Accuracy52.7—Unverified
10IXC-2.5 7BAverage Accuracy51.6—Unverified
#ModelMetricClaimedVerifiedStatus
1LinVT-Qwen2-VL (7B)Avg.69.3—Unverified
2Tarsier (34B)Avg.67.6—Unverified
3InternVideo2Avg.67.2—Unverified
4LongVU (7B)Avg.66.9—Unverified
5Oryx(34B)Avg.64.7—Unverified
6VideoLLaMA2 (72B)Avg.62—Unverified
7VideoChat-T (7B)Avg.59.9—Unverified
8mPLUG-Owl3(7B)Avg.59.5—Unverified
9PPLLaVA (7b)Avg.59.2—Unverified
10VideoGPT+Avg.58.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Mirasol3BAccuracy50.42—Unverified
2VASTAccuracy50.1—Unverified
3COSAAccuracy49.2—Unverified
4VALORAccuracy49.2—Unverified
5MA-LMMAccuracy48.5—Unverified
6mPLUG-2Accuracy48—Unverified
7FrozenBiLMAccuracy47—Unverified
8HBIAccuracy46.2—Unverified
9EMCL-NetAccuracy45.8—Unverified
10VindLUAccuracy44.6—Unverified
#ModelMetricClaimedVerifiedStatus
1VLAP (4 frames)Average Accuracy67.1—Unverified
2LLaMA-VQAAverage Accuracy65.4—Unverified
3SeViLAAverage Accuracy64.9—Unverified
4InternVideoAverage Accuracy58.7—Unverified
5GF(sup)Average Accuracy53.94—Unverified
6GF(uns)Average Accuracy53.86—Unverified
7MISTAverage Accuracy51.13—Unverified
8Temp[ATP]Average Accuracy48.37—Unverified
9AnyMAL-70B (0-shot)Average Accuracy48.2—Unverified
10All-in-oneAverage Accuracy47.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Seed1.5-VLAVG60—Unverified
2VideoChat-Online (4B)AVG54.9—Unverified
3Gemini-1.5-FlashAVG50.7—Unverified
4Qwen2-VL (7B)AVG49.7—Unverified
5LLaVA-OneVision (7B)AVG49.5—Unverified
6InternVL2 (7B)AVG48.7—Unverified
7InternVL2 (4B)AVG44.1—Unverified
8LongVA (7B)AVG43.6—Unverified
9LLaMA-VID (7B)AVG41.9—Unverified
10MiniCPM-V 2.6 (7B)AVG39.1—Unverified
#ModelMetricClaimedVerifiedStatus
1GF (sup) - Faster RCNNAverage Accuracy55.08—Unverified
2MIST - CLIPAverage Accuracy54.39—Unverified
3GF (uns) - S3DAverage Accuracy53.33—Unverified
4SViTTAverage Accuracy52.7—Unverified
5MIST - AIOAverage Accuracy50.96—Unverified
6SHG-VQA (trained from scratch)Average Accuracy49.2—Unverified
7AIO - ViTAverage Accuracy48.59—Unverified
8MMTFAverage Accuracy44.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Text + Text (no Multimodal Pretext Training)Accuracy93.2—Unverified
2FrozenBiLMAccuracy86.7—Unverified
3Just AskAccuracy84.4—Unverified
4SeViLAAccuracy83.7—Unverified
5Hero w/ pre-trainingAccuracy77.75—Unverified
6ATPAccuracy65.1—Unverified
7FrozenBiLM (0-shot)Accuracy58.4—Unverified
8Just Ask (0-shot)Accuracy51.1—Unverified