Papers Generalized Referring Expression Segmentation
“Generalized Referring Expression Segmentation” 태그가 달린 논문 18편 · 필터 해제
GREx: Generalized Referring Expression Segmentation, Comprehension, and Generation
Referring Expression Segmentation (RES) and Comprehension (REC) respectively segment and detect the object described by an expression, while Referring Expression Generation (REG) generates an expression for the selected …
Generalized Referring Expression SegmentationReferring expression generationGeneralized Referring Expression Segmentation on Aerial Photos
Referring expression segmentation is a fundamental task in computer vision that integrates natural language understanding with precise visual localization of target regions. Considering aerial imagery (e.g., modern aeria…
Generalized Referring Expression SegmentationNatural Language UnderstandingSemantic SegmentationVisual LocalizationLatent Expression Generation for Referring Image Segmentation and Grounding
Visual grounding tasks, such as referring image segmentation (RIS) and referring expression comprehension (REC), aim to localize a target object based on a given textual description. The target object in an image can be …
Generalized Referring Expression SegmentationContrastive LearningImage SegmentationVisual GroundingDeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback Synergy
Referring Image Segmentation (RIS) is a challenging task that aims to segment objects in an image based on natural language expressions. While prior studies have predominantly concentrated on improving vision-language in…
Data AugmentationGeneralized Referring Expression SegmentationImage SegmentationReading Comprehension+2Refer to Anything with Vision-Language Prompts
Recent image segmentation models have advanced to segment images into high-quality masks for visual entities, and yet they cannot provide comprehensive semantic understanding for complex queries based on both language an…
BenchmarkingGeneralized Referring Expression SegmentationImage SegmentationReferring Expression+3Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension
In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuses on single-target expressions, GREC ext…
Generalized Referring Expression ComprehensionGeneralized Referring Expression SegmentationObject CountingPhrase Grounding+3Instance-Aware Generalized Referring Expression Segmentation
Recent works on Generalized Referring Expression Segmentation (GRES) struggle with handling complex expressions referring to multiple distinct objects. This is because these methods typically employ an end-to-end foregro…
Generalized Referring Expression SegmentationObjectReferring ExpressionReferring Expression Segmentation+1CoHD: A Counting-Aware Hierarchical Decoding Framework for Generalized Referring Expression Segmentation
The newly proposed Generalized Referring Expression Segmentation (GRES) amplifies the formulation of classic RES by involving complex multiple/non-target scenarios. Recent approaches address GRES by directly extending th…
Generalized Referring Expression SegmentationObjectReferring ExpressionReferring Expression Segmentation+1Bring Adaptive Binding Prototypes to Generalized Referring Expression Segmentation
Referring Expression Segmentation (RES) has attracted rising attention, aiming to identify and segment objects based on natural language expressions. While substantial progress has been made in RES, the emergence of Gene…
DecoderGeneralized Referring Expression SegmentationReferring ExpressionReferring Expression SegmentationPSALM: Pixelwise SegmentAtion with Large Multi-Modal Model
PSALM is a powerful extension of the Large Multi-modal Model (LMM) to address the segmentation task challenges. To overcome the limitation of the LMM being limited to textual output, PSALM incorporates a mask decoder and…
DecoderGeneralized Referring Expression SegmentationImage SegmentationPanoptic Segmentation+6GROUNDHOG: Grounding Large Language Models to Holistic Segmentation
Most multimodal large language models (MLLMs) learn language-to-object grounding through causal language modeling where grounded objects are captured by bounding boxes as sequences of location tokens. This paradigm lacks…
Causal Language ModelingGeneralized Referring Expression SegmentationHallucinationLanguage Modeling+3GSVA: Generalized Segmentation via Multimodal Large Language Models
Generalized Referring Expression Segmentation (GRES) extends the scope of classic RES to refer to multiple objects in one expression or identify the empty targets absent in the image. GRES poses challenges in modeling th…
DecoderGeneralized Referring Expression SegmentationReferring ExpressionReferring Expression Segmentation+1GRES: Generalized Referring Expression Segmentation
Referring Expression Segmentation (RES) aims to generate a segmentation mask for the object described by a given language expression. Existing classic RES datasets and methods commonly support single-target expressions o…
Generalized Referring Expression SegmentationReferring ExpressionReferring Expression SegmentationSegmentationLAVT: Language-Aware Vision Transformer for Referring Image Segmentation
Referring image segmentation is a fundamental vision-language task that aims to segment out an object referred to by a natural language expression from an image. One of the key challenges behind this task is leveraging t…
DecoderGeneralized Referring Expression SegmentationImage SegmentationReferring Expression+2CRIS: CLIP-Driven Referring Image Segmentation
Referring image segmentation aims to segment a referent via a natural linguistic expression.Due to the distinct data properties between text and image, it is challenging for a network to well align text and pixel-level f…
Contrastive LearningDecoderGeneralized Referring Expression SegmentationImage Segmentation+3Vision-Language Transformer and Query Generation for Referring Segmentation
In this work, we address the challenging task of referring segmentation. The query expression in referring segmentation typically indicates the target object by describing its relationship with others. Therefore, to find…
DecoderGeneralized Referring Expression ComprehensionGeneralized Referring Expression SegmentationReferring Expression Segmentation+1Locate then Segment: A Strong Pipeline for Referring Image Segmentation
Referring image segmentation aims to segment the objects referred by a natural language expression. Previous methods usually focus on designing an implicit and recurrent feature interaction mechanism to fuse the visual-l…
Generalized Referring Expression SegmentationImage SegmentationSegmentationSemantic SegmentationMAttNet: Modular Attention Network for Referring Expression Comprehension
In this paper, we address referring expression comprehension: localizing an image region described by a natural language expression. While most recent work treats expressions as a single unit, we propose to decompose the…
Generalized Referring Expression SegmentationReferring ExpressionReferring Expression ComprehensionReferring Expression Segmentation