Browse State-of-the-Art › Referring Expression Comprehension
Referring Expression Comprehension
98 papers with code · 0 benchmarks · 12 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
12 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 98 papers with code (167 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
17 Apr 2023 13 repositories listed Syntology ran 16 of 51 samples · 35 unverifiedInstruction 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.
-
6 Aug 2019 11 repositories listed Syntology ran 10 of 34 samples · 24 unverified · 34 pointer-only (licence)We present ViLBERT (short for Vision-and-Language BERT), a model for learning task-agnostic joint representations of image content and natural language.
-
9 Mar 2023 10 repositories listed Syntology ran 2 of 5 samples · 3 unverifiedTo 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…
-
8 Mar 2018 10 repositories listed Syntology ran 1 of 7 samples · 6 unverifiedWe present the MAC network, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning.
-
5 Oct 2023 9 repositories listed Syntology ran 6 of 9 samples · 3 unverified · 8 pointer-only (licence)Large multimodal models (LMM) have recently shown encouraging progress with visual instruction tuning.
-
25 Sep 2019 7 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i.
-
26 Apr 2021 5 repositories listed Syntology ran 6 of 11 samples · 5 unverifiedWe also investigate the utility of our model as an object detector on a given label set when fine-tuned in a few-shot setting.
-
28 Dec 2024 4 repositories listed Syntology ran 9 of 15 samples · 6 unverified · 3 pointer-only (licence)Finally, we outline the challenges confronting visual grounding and propose valuable directions for future research, which may serve as inspiration for subsequent researchers.
-
17 Oct 2023 4 repositories listed Syntology ran 0 of 1 samples · 1 unverifiedWe 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.
-
7 Feb 2022 4 repositories listed Syntology ran 1 of 1 samples · 0 unverifiedIn this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization.
-
30 Mar 2022 3 repositories listed Syntology ran 1 of 4 samples · 3 unverifiedIn this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e.
-
22 Aug 2019 3 repositories listed Syntology ran 0 of 1 samples · 1 unverifiedWe introduce a new pre-trainable generic representation for visual-linguistic tasks, called Visual-Linguistic BERT (VL-BERT for short).
-
3 Jan 2019 3 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)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.
-
27 Mar 2024 2 repositories listed Syntology ran 7 of 8 samples · 1 unverifiedWe try to narrow the gap by mining the potential of VLMs for better performance and any-to-any workflow from three aspects, i.
-
15 Feb 2024 2 repositories listedGrounded Multimodal Named Entity Recognition (GMNER) is a nascent multimodal task that aims to identify named entities, entity types and their corresponding visual regions.
-
4 Jan 2024 2 repositories listed Syntology ran 4 of 6 samples · 2 unverifiedGrounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Expression Comprehension (REC).
-
14 Oct 2023 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)Motivated by this, we target to build a unified interface for completing many vision-language tasks including image description, visual question answering, and visual grounding, among others.
-
26 Jun 2023 2 repositories listedWe introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e.
-
18 May 2023 2 repositories listed Syntology ran 2 of 7 samples · 5 unverifiedIn this work, we explore a scalable way for building a general representation model toward unlimited modalities.
-
12 Apr 2022 2 repositories listed Syntology ran 0 of 5 samples · 5 unverifiedTraining a referring expression comprehension (ReC) model for a new visual domain requires collecting referring expressions, and potentially corresponding bounding boxes, for images in the domain.
-
17 Apr 2021 2 repositories listed Syntology ran 6 of 20 samples · 14 unverifiedIn this paper, we present a neat yet effective transformer-based framework for visual grounding, namely TransVG, to address the task of grounding a language query to the corresponding region onto an image.
-
4 Feb 2021 2 repositories listed Syntology ran 2 of 12 samples · 10 unverifiedOn 7 popular vision-and-language benchmarks, including visual question answering, referring expression comprehension, visual commonsense reasoning, most of which have been previously modeled as discriminative tasks, our…
-
11 Jun 2020 2 repositories listed Syntology ran 10 of 20 samples · 10 unverified · 6 pointer-only (licence)We present VILLA, the first known effort on large-scale adversarial training for vision-and-language (V+L) representation learning.
-
19 Mar 2020 2 repositories listed Syntology ran 0 of 13 samples · 13 unverifiedIn addition, we address a key challenge in this multi-task setup, i.
-
18 Aug 2019 2 repositories listed Syntology ran 1 of 19 samples · 18 unverifiedWe propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight.
-
30 Dec 2016 2 repositories listedThe speaker generates referring expressions, the listener comprehends referring expressions, and the reinforcer introduces a reward function to guide sampling of more discriminative expressions.
-
29 May 2025 1 repository listedImage-text models excel at image-level tasks but struggle with detailed visual understanding.
-
10 Apr 2025 1 repository listedMotivated by this observation, we investigate the extension of R1-style reinforcement learning to Vision-Language Models (VLMs), aiming to enhance their visual reasoning capabilities.
-
27 Feb 2025 1 repository listedTo address fine-grained compositional REC, we propose novel methods based on a Specialist-MLLM collaboration framework, leveraging the complementary strengths of them: Specialist Models handle simpler tasks efficiently,…
-
1 Feb 2025 1 repository listedNGDINO explicitly learns and utilizes the number of objects referred to in the expression.
Syntology lines on 23 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections