Papers Object Counting
“Object Counting” 태그가 달린 논문 214편 · 필터 해제
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
Low-shot object counters estimate the number of objects in an image using few or no annotated exemplars. Objects are localized by matching them to prototypes, which are constructed by unsupervised image-wide object appea…
Exemplar-Free CountingFew-shot Object Counting and DetectionObjectObject Counting+3Mind the Prompt: A Novel Benchmark for Prompt-based Class-Agnostic Counting
Recently, object counting has shifted towards class-agnostic counting (CAC), which counts instances of arbitrary object classes never seen during model training. With advancements in robust vision-and-language foundation…
ObjectObject CountingGCA-SUNet: A Gated Context-Aware Swin-UNet for Exemplar-Free Counting
Exemplar-Free Counting aims to count objects of interest without intensive annotations of objects or exemplars. To achieve this, we propose a Gated Context-Aware Swin-UNet (GCA-SUNet) to directly map an input image to th…
DecoderExemplar-FreeExemplar-Free CountingObject Counting+1Dense Center-Direction Regression for Object Counting and Localization with Point Supervision
Object counting and localization problems are commonly addressed with point supervised learning, which allows the use of less labor-intensive point annotations. However, learning based on point annotations poses challeng…
ObjectObject CountingregressionDetection-Driven Object Count Optimization for Text-to-Image Diffusion Models
Accurately controlling object count in text-to-image generation remains a key challenge. Supervised methods often fail, as training data rarely covers all count variations. Methods that manipulate the denoising process t…
DenoisingImage GenerationObjectObject Counting+2Mutually-Aware Feature Learning for Few-Shot Object Counting
Few-shot object counting has garnered significant attention for its practicality as it aims to count target objects in a query image based on given exemplars without the need for additional training. However, there is a …
Object CountingZero-shot Object Counting with Good Exemplars
Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a critical challenge in current ZOC methods lie…
Contrastive LearningObjectObject CountingZero-Shot CountingCountGD: Multi-Modal Open-World Counting
The goal of this paper is to improve the generality and accuracy of open-vocabulary object counting in images. To improve the generality, we repurpose an open-vocabulary detection foundation model (GroundingDINO) for the…
Object CountingOpen-vocabulary object countingZero-Shot CountingRS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
The unprecedented advancements in Multimodal Large Language Models (MLLMs) have demonstrated strong potential in interacting with humans through both language and visual inputs to perform downstream tasks such as visual …
AI AgentDescriptiveInstruction FollowingLanguage Modeling+10Learning Spatial Similarity Distribution for Few-shot Object Counting
Few-shot object counting aims to count the number of objects in a query image that belong to the same class as the given exemplar images. Existing methods compute the similarity between the query image and exemplars in t…
Object CountingOverconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models
Language and Vision-Language Models (LLMs/VLMs) have revolutionized the field of AI by their ability to generate human-like text and understand images, but ensuring their reliability is crucial. This paper aims to evalua…
Object CountingDAVE -- A Detect-and-Verify Paradigm for Low-Shot Counting
Low-shot counters estimate the number of objects corresponding to a selected category, based on only few or no exemplars annotated in the image. The current state-of-the-art estimates the total counts as the sum over the…
Exemplar-Free CountingFew-shot Object Counting and DetectionObjectObject Counting+1ChatGPT and general-purpose AI count fruits in pictures surprisingly well
Object counting is a popular task in deep learning applications in various domains, including agriculture. A conventional deep learning approach requires a large amount of training data, often a logistic problem in a rea…
Deep LearningFew-Shot LearningObject CountingCounting Objects in a Robotic Hand
A robot performing multi-object grasping needs to sense the number of objects in the hand after grasping. The count plays an important role in determining the robot's next move and the outcome and efficiency of the whole…
Contrastive LearningObjectObject CountingChange-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
Monitoring changes in the Earth's surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Remote sensing satellite imagery offers a …
Change DetectionLanguage ModellingLarge Language ModelObject CountingFew-shot Object Localization
Existing object localization methods are tailored to locate specific classes of objects, relying heavily on abundant labeled data for model optimization. However, acquiring large amounts of labeled data is challenging in…
Model OptimizationObjectObject CountingObject LocalizationGriffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referring
Large Vision Language Models have achieved fine-grained object perception, but the limitation of image resolution remains a significant obstacle to surpass the performance of task-specific experts in complex and dense sc…
ObjectObject Countingobject-detectionObject Detection+1TFCounter:Polishing Gems for Training-Free Object Counting
Object counting is a challenging task with broad application prospects in security surveillance, traffic management, and disease diagnosis. Existing object counting methods face a tri-fold challenge: achieving superior p…
ManagementObjectObject CountingTraining-free Object CountingOmniCount: Multi-label Object Counting with Semantic-Geometric Priors
Object counting is pivotal for understanding the composition of scenes. Previously, this task was dominated by class-specific methods, which have gradually evolved into more adaptable class-agnostic strategies. However, …
ObjectObject CountingOpen-vocabulary object countingTraining-free Object Counting+1Effectiveness Assessment of Recent Large Vision-Language Models
The advent of large vision-language models (LVLMs) represents a remarkable advance in the quest for artificial general intelligence. However, the model's effectiveness in both specialized and general tasks warrants furth…
Anomaly DetectionAttributeHallucinationLesion Detection+6