Visual Question Answering (VQA) on CLEVR

Metric: Accuracy (higher is better)

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	NS-VQA (1K programs)	99.8	No	Neural-Symbolic VQA: Disentangling Reasoning fro...	2018-10-04	Code
2	MDETR	99.7	No	MDETR -- Modulated Detection for End-to-End Mult...	2021-04-26	Code
3	NeSyCoCo	99.7	No	NeSyCoCo: A Neuro-Symbolic Concept Composer for ...	2024-12-20	Code
4	NeSyCoCo Neuro-Symbolic	99.7	No	NeSyCoCo: A Neuro-Symbolic Concept Composer for ...	2024-12-20	Code
5	OCCAM (ours)	99.4	No	Interpretable Visual Reasoning via Induced Symbo...	2020-11-23	Code
6	TbD + reg + hres	99.1	No	Transparency by Design: Closing the Gap Between ...	2018-03-14	Code
7	NS-CL	98.9	No	The Neuro-Symbolic Concept Learner: Interpreting...	2019-04-26	Code
8	MAC	98.9	No	Compositional Attention Networks for Machine Rea...	2018-03-08	Code
9	CNN + LSTM + RN + HAN	98.8	No	Learning Visual Question Answering by Bootstrapp...	2018-08-01	Code
10	DDRprog*	98.3	No	DDRprog: A CLEVR Differentiable Dynamic Reasonin...	2018-03-30	-
11	single-hop + LCGN (ours)	97.9	No	Language-Conditioned Graph Networks for Relation...	2019-05-10	Code
12	CNN+GRU+FiLM	97.7	No	FiLM: Visual Reasoning with a General Conditioni...	2017-09-22	Code
13	XNM-Det supervised	97.7	No	Explainable and Explicit Visual Reasoning over S...	2018-12-05	Code
14	IEP-700K	96.9	No	Inferring and Executing Programs for Visual Reas...	2017-05-10	Code
15	CNN + LSTM + RN	95.5	No	A simple neural network module for relational re...	2017-06-05	Code
16	QGHC+Att+Concat	65.9	No	Question-Guided Hybrid Convolution for Visual Qu...	2018-08-08	-