| VLAB |
- Accuracy
- 0.496
|
VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending 2023-05-22 |
연결 없음 |
| MaMMUT |
- Accuracy
- 0.495
|
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks 2023-03-29 |
코드 1 |
| mPLUG-2 |
- Accuracy
- 0.480
|
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video 2023-02-01 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| MuLTI |
- Accuracy
- 0.478
|
MuLTI: Efficient Video-and-Language Understanding with Text-Guided MultiWay-Sampler and Multiple Choice Modeling 2023-03-10 |
연결 없음 |
| Flamingo |
- Accuracy
- 0.474
|
Flamingo: a Visual Language Model for Few-Shot Learning 2022-04-29 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| InternVideo |
- Accuracy
- 0.471
|
InternVideo: General Video Foundation Models via Generative and Discriminative Learning 2022-12-06 |
코드 1 · 코드 2 |
| UMT-L (ViT-L/16) |
- Accuracy
- 0.471
|
Unmasked Teacher: Towards Training-Efficient Video Foundation Models 2023-03-28 |
코드 1 |
| FrozenBiLM+ |
- Accuracy
- 0.470
|
Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models 2023-08-18 |
코드 1 |
| vid-TLDR (UMT-L) |
- Accuracy
- 0.470
|
vid-TLDR: Training Free Token merging for Light-weight Video Transformer 2024-03-20 |
코드 1 |
| VideoCoCa |
- Accuracy
- 0.463
|
VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners 2022-12-09 |
연결 없음 |
| HBI |
- Accuracy
- 0.462
|
Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning 2023-03-25 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| HiTeA |
- Accuracy
- 0.459
|
HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training 2022-12-30 |
연결 없음 |
| EMCL-Net |
- Accuracy
- 0.458
|
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations 2022-11-21 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| Co-Tokenization |
- Accuracy
- .457
|
Video Question Answering with Iterative Video-Text Co-Tokenization 2022-08-01 |
연결 없음 |
| X2-VLM (large) |
- Accuracy
- 0.455
|
X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks 2022-11-22 |
코드 1 · 코드 2 |
| X2-VLM (base) |
- Accuracy
- 0.45
|
X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks 2022-11-22 |
코드 1 · 코드 2 |
| All-in-one-B |
- Accuracy
- 0.443
|
All in One: Exploring Unified Video-Language Pre-training 2022-03-14 |
코드 1 |
| OmniVL |
- Accuracy
- 0.441
|
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks 2022-09-15 |
연결 없음 |
| Clover |
- Accuracy
- 0.441
|
Clover: Towards A Unified Video-Language Alignment and Fusion Model 2022-07-16 |
코드 1 |
| AIO+MIF |
- Accuracy
- 0.440
|
Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models 2023-07-09 |
코드 1 · 코드 2 |
| AIO+MDF |
- Accuracy
- 0.438
|
Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models 2023-07-09 |
코드 1 · 코드 2 |
| GIT+MDF |
- Accuracy
- 0.423
|
Self-Adaptive Sampling for Efficient Video Question-Answering on Image--Text Models 2023-07-09 |
코드 1 · 코드 2 |
| ALPRO |
- Accuracy
- 0.421
|
Align and Prompt: Video-and-Language Pre-training with Entity Prompts 2021-12-17 |
코드 1 |
| LRCE |
- Accuracy
- 0.42
|
Lightweight Recurrent Cross-modal Encoder for Video Question Answering 2023-06-30 |
코드 1 |
| JustAsk+ |
- Accuracy
- 0.418
|
Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models 2023-08-18 |
코드 1 |
| All-in-one+ |
- Accuracy
- 0.395
|
Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models 2023-08-18 |
코드 1 |
| CLIPBERT |
- Accuracy
- 0.374
|
Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling 2021-02-11 |
코드 1 |
| HCRN |
- Accuracy
- 0.356
|
Hierarchical Conditional Relation Networks for Video Question Answering 2020-02-25 |
코드 1 |
| DualVGR |
- Accuracy
- 0.355
|
DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering 2021-07-10 |
코드 1 |
| HMEMA |
- Accuracy
- 0.33
|
Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering 2019-04-08 |
코드 1 |