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Visual Reasoning

27 papers with code · Reasoning

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Are Disentangled Representations Helpful for Abstract Visual Reasoning?

NeurIPS 2019 google-research/disentanglement_lib

A disentangled representation encodes information about the salient factors of variation in the data independently.

VISUAL REASONING

Learning by Abstraction: The Neural State Machine

NeurIPS 2019 stanfordnlp/mac-network

We introduce the Neural State Machine, seeking to bridge the gap between the neural and symbolic views of AI and integrate their complementary strengths for the task of visual reasoning.

VISUAL QUESTION ANSWERING VISUAL REASONING

Compositional Attention Networks for Machine Reasoning

ICLR 2018 stanfordnlp/mac-network

We present the MAC network, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning.

VISUAL REASONING

LXMERT: Learning Cross-Modality Encoder Representations from Transformers

IJCNLP 2019 airsplay/lxmert

In LXMERT, we build a large-scale Transformer model that consists of three encoders: an object relationship encoder, a language encoder, and a cross-modality encoder.

LANGUAGE MODELLING QUESTION ANSWERING VISUAL QUESTION ANSWERING VISUAL REASONING

Learning to Compose Dynamic Tree Structures for Visual Contexts

CVPR 2019 KaihuaTang/Scene-Graph-Benchmark.pytorch

We propose to compose dynamic tree structures that place the objects in an image into a visual context, helping visual reasoning tasks such as scene graph generation and visual Q&A.

 SOTA for Visual Question Answering on VQA v2 (Percentage correct metric )

GRAPH GENERATION SCENE GRAPH GENERATION VISUAL QUESTION ANSWERING VISUAL REASONING

VisualBERT: A Simple and Performant Baseline for Vision and Language

9 Aug 2019uclanlp/visualbert

We propose VisualBERT, a simple and flexible framework for modeling a broad range of vision-and-language tasks.

LANGUAGE MODELLING VISUAL QUESTION ANSWERING VISUAL REASONING

FiLM: Visual Reasoning with a General Conditioning Layer

22 Sep 2017ethanjperez/film

We introduce a general-purpose conditioning method for neural networks called FiLM: Feature-wise Linear Modulation.

VISUAL REASONING

Inferring and Executing Programs for Visual Reasoning

ICCV 2017 ethanjperez/film

Existing methods for visual reasoning attempt to directly map inputs to outputs using black-box architectures without explicitly modeling the underlying reasoning processes.

VISUAL REASONING

CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

CVPR 2017 ethanjperez/film

When building artificial intelligence systems that can reason and answer questions about visual data, we need diagnostic tests to analyze our progress and discover shortcomings.

QUESTION ANSWERING VISUAL QUESTION ANSWERING VISUAL REASONING

Object Level Visual Reasoning in Videos

ECCV 2018 fabienbaradel/object_level_visual_reasoning

Human activity recognition is typically addressed by detecting key concepts like global and local motion, features related to object classes present in the scene, as well as features related to the global context.

HUMAN ACTIVITY RECOGNITION OBJECT DETECTION VISUAL REASONING