Papers Co-Salient Object Detection
“Co-Salient Object Detection” 태그가 달린 논문 46편 · 필터 해제
TF-SSD: A Strong Pipeline via Synergic Mask Filter for Training-free Co-salient Object Detection
Co-salient Object Detection (CoSOD) aims to segment salient objects that consistently appear across a group of related images. Despite the notable progress achieved by recent training-based approaches, they still remain …
Co-Salient Object DetectionSaliency-R1: Incentivizing Unified Saliency Reasoning Capability in MLLM with Confidence-Guided Reinforcement Learning
Although multimodal large language models (MLLMs) excel in high-level vision-language reasoning, they lack inherent awareness of visual saliency, making it difficult to identify key visual elements. To bridge this gap, w…
Co-Salient Object DetectionReinforcement LearningInstance SegmentationVisual Consensus Prompting for Co-Salient Object Detection
Existing co-salient object detection (CoSOD) methods generally employ a three-stage architecture (i.e., encoding, consensus extraction & dispersion, and prediction) along with a typical full fine-tuning paradigm. Althoug…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionCONDA: Condensed Deep Association Learning for Co-Salient Object Detection
Inter-image association modeling is crucial for co-salient object detection. Despite satisfactory performance, previous methods still have limitations on sufficient inter-image association modeling. Because most of them …
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object Detection+1CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
Co-salient object detection (CoSOD) aims to identify the common and salient (usually in the foreground) regions across a given group of images. Although achieving significant progress, state-of-the-art CoSODs could be ea…
Adversarial AttackCo-Salient Object Detectionobject-detectionObject Detection+2Self-supervised co-salient object detection via feature correspondence at multiple scales
Our paper introduces a novel two-stage self-supervised approach for detecting co-occurring salient objects (CoSOD) in image groups without requiring segmentation annotations. Unlike existing unsupervised methods that rel…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionDiscriminative Consensus Mining with A Thousand Groups for More Accurate Co-Salient Object Detection
Co-Salient Object Detection (CoSOD) is a rapidly growing task, extended from Salient Object Detection (SOD) and Common Object Segmentation (Co-Segmentation). It is aimed at detecting the co-occurring salient object in th…
Co-Salient Object DetectionObjectobject-detectionObject Detection+2Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
In this paper, we address the detection of co-occurring salient objects (CoSOD) in an image group using frequency statistics in an unsupervised manner, which further enable us to develop a semi-supervised method. While p…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionTowards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-Masking
The traditional definition of co-salient object detection (CoSOD) task is to segment the common salient objects in a group of relevant images. This definition is based on an assumption of group consensus consistency that…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionCo-Salient Object Detection with Semantic-Level Consensus Extraction and Dispersion
Given a group of images, co-salient object detection (CoSOD) aims to highlight the common salient object in each image. There are two factors closely related to the success of this task, namely consensus extraction, and …
Co-Salient Object DetectionDecoderObjectobject-detection+2Zero-Shot Co-salient Object Detection Framework
Co-salient Object Detection (CoSOD) endeavors to replicate the human visual system's capacity to recognize common and salient objects within a collection of images. Despite recent advancements in deep learning models, th…
Co-Salient Object DetectionObjectobject-detectionObject Detection+1Advancing Referring Expression Segmentation Beyond Single Image
Referring Expression Segmentation (RES) is a widely explored multi-modal task, which endeavors to segment the pre-existing object within a single image with a given linguistic expression. However, in broader real-world s…
Co-Salient Object DetectionObjectobject-detectionObject Detection+3SegGPT Meets Co-Saliency Scene
Co-salient object detection targets at detecting co-existed salient objects among a group of images. Recently, a generalist model for segmenting everything in context, called SegGPT, is gaining public attention. In view …
Co-Salient Object DetectionObjectobject-detectionObject Detection+1Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Most previous co-salient object detection works mainly focus on extracting co-salient cues via mining the consistency relations across images while ignoring explicit exploration of background regions. In this paper, we p…
Computational EfficiencyCo-Salient Object Detectionobject-detectionObject Detection+2Co-Salient Object Detection with Co-Representation Purification
Co-salient object detection (Co-SOD) aims at discovering the common objects in a group of relevant images. Mining a co-representation is essential for locating co-salient objects. Unfortunately, the current Co-SOD method…
Co-Salient Object DetectionObjectobject-detectionObject Detection+1Memory-aided Contrastive Consensus Learning for Co-salient Object Detection
Co-Salient Object Detection (CoSOD) aims at detecting common salient objects within a group of relevant source images. Most of the latest works employ the attention mechanism for finding common objects. To achieve accura…
Co-Salient Object Detectionobject-detectionObject DetectionSalient Object DetectionCo-Salient Object Detection With Uncertainty-Aware Group Exchange-Masking
The traditional definition of co-salient object detection (CoSOD) task is to segment the common salient objects in a group of relevant images. Existing CoSOD models by default adopt the group consensus assumption. Th…
Co-Salient Object DetectionDecoderobject-detectionObject Detection+3Generalised Co-Salient Object Detection
We propose a new setting that relaxes an assumption in the conventional Co-Salient Object Detection (CoSOD) setting by allowing the presence of "noisy images" which do not show the shared co-salient object. We call this …
Co-Salient Object DetectionObjectobject-detectionObject Detection+2GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in natural scenes. The proposed GCoNet+ achie…
Co-Salient Object DetectionObjectobject-detectionObject Detection+2Global-and-Local Collaborative Learning for Co-Salient Object Detection
The goal of co-salient object detection (CoSOD) is to discover salient objects that commonly appear in a query group containing two or more relevant images. Therefore, how to effectively extract inter-image correspondenc…
8kCo-Salient Object Detectionobject-detectionObject Detection+1