Referring Expression Comprehension
96 papers with code • 10 benchmarks • 12 datasets
Benchmarks
These leaderboards are used to track progress in Referring Expression Comprehension
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Libraries
Use these libraries to find Referring Expression Comprehension models and implementationsDatasets
RefCOCO
Google Refexp
Talk2Car
GRIT
Description Detection Dataset
A Game Of Sorts
Most implemented papers
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
facebookresearch/vilbert-multi-task
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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.
Visual Instruction Tuning
haotian-liu/LLaVA
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NeurIPS 2023
Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field.
Compositional Attention Networks for Machine Reasoning
stanfordnlp/mac-network
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ICLR 2018
We present the MAC network, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning.
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
idea-research/groundingdino
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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.
UNITER: UNiversal Image-TExt Representation Learning
ChenRocks/UNITER
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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).
Improved Baselines with Visual Instruction Tuning
huggingface/transformers
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CVPR 2024
Large multimodal models (LMM) have recently shown encouraging progress with visual instruction tuning.
MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
ashkamath/mdetr
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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.
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
ofa-sys/ofa
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In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization.
Towards Visual Grounding: A Survey
linhuixiao/awesome-visual-grounding
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Finally, we outline the challenges confronting visual grounding and propose valuable directions for future research, which may serve as inspiration for subsequent researchers.
CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions
ruotianluo/iep-ref
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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.
