Referring Expression Comprehension

69 papers with code • 8 benchmarks • 8 datasets

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Use these libraries to find Referring Expression Comprehension models and implementations

Most implemented papers

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

facebookresearch/vilbert-multi-task NeurIPS 2019

We present ViLBERT (short for Vision-and-Language BERT), a model for learning task-agnostic joint representations of image content and natural language.

Compositional Attention Networks for Machine Reasoning

stanfordnlp/mac-network ICLR 2018

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

UNITER: UNiversal Image-TExt Representation Learning

ChenRocks/UNITER ECCV 2020

Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).

Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

idea-research/groundingdino 9 Mar 2023

To effectively fuse language and vision modalities, we conceptually divide a closed-set detector into three phases and propose a tight fusion solution, which includes a feature enhancer, a language-guided query selection, and a cross-modality decoder for cross-modality fusion.

OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

ofa-sys/ofa 7 Feb 2022

In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization.

CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

ruotianluo/iep-ref CVPR 2019

Yet there has been evidence that current benchmark datasets suffer from bias, and current state-of-the-art models cannot be easily evaluated on their intermediate reasoning process.

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

jackroos/VL-BERT ICLR 2020

We introduce a new pre-trainable generic representation for visual-linguistic tasks, called Visual-Linguistic BERT (VL-BERT for short).

MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding

ashkamath/mdetr 26 Apr 2021

We also investigate the utility of our model as an object detector on a given label set when fine-tuned in a few-shot setting.

SeqTR: A Simple yet Universal Network for Visual Grounding

sean-zhuh/seqtr 30 Mar 2022

In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e. g., phrase localization, referring expression comprehension (REC) and segmentation (RES).

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

microsoft/SoM 17 Oct 2023

We present Set-of-Mark (SoM), a new visual prompting method, to unleash the visual grounding abilities of large multimodal models (LMMs), such as GPT-4V.