Papers Object Counting
“Object Counting” 태그가 달린 논문 214편 · 필터 해제
Expanding Zero-Shot Object Counting with Rich Prompts
Expanding pre-trained zero-shot counting models to handle unseen categories requires more than simply adding new prompts, as this approach does not achieve the necessary alignment between text and visual features for acc…
ObjectObject CountingZero-Shot CountingVisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning
Large vision-language models exhibit inherent capabilities to handle diverse visual perception tasks. In this paper, we introduce VisionReasoner, a unified framework capable of reasoning and solving multiple visual perce…
2D Object DetectionObject CountingReasoning SegmentationReferring Expression Segmentation+4Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?
The 180x360 omnidirectional field of view captured by 360-degree cameras enables their use in a wide range of applications such as embodied AI and virtual reality. Although recent advances in multimodal large language mo…
HallucinationObject CountingSpatial ReasoningLearning What NOT to Count
Few/zero-shot object counting methods reduce the need for extensive annotations but often struggle to distinguish between fine-grained categories, especially when multiple similar objects appear in the same scene. To add…
Object CountingZero-Shot CountingMarmot: Multi-Agent Reasoning for Multi-Object Self-Correcting in Improving Image-Text Alignment
While diffusion models excel at generating high-quality images, they often struggle with accurate counting, attributes, and spatial relationships in complex multi-object scenes. One potential approach is to utilize Multi…
AI AgentAttributeImage GenerationLarge Language Model+3MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams
Diagrams serve as a fundamental form of visual language, representing complex concepts and their inter-relationships through structured symbols, shapes, and spatial arrangements. Unlike natural images, their inherently s…
Mathematical ReasoningObject CountingA Causal Lens for Evaluating Faithfulness Metrics
Large Language Models (LLMs) offer natural language explanations as an alternative to feature attribution methods for model interpretability. However, despite their plausibility, they may not reflect the model's internal…
Decision MakingFact CheckingModel EditingObject CountingWhy Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding
Vision Language Models (VLMs) have achieved remarkable progress in multimodal tasks, yet they often struggle with visual arithmetic, seemingly simple capabilities like object counting or length comparison, which are esse…
Arithmetic ReasoningChart UnderstandingDecoderMath+1FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting
In class-agnostic object counting, the goal is to estimate the total number of object instances in an image without distinguishing between specific categories. Existing methods often predict this count without considerin…
ObjectObject CountingSAVE: Self-Attention on Visual Embedding for Zero-Shot Generic Object Counting
Zero-shot counting is a subcategory of Generic Visual Object Counting, which aims to count objects from an arbitrary class in a given image. While few-shot counting relies on delivering exemplars to the model to count si…
Exemplar-Free CountingObjectObject CountingZero-Shot CountingAquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis
The preservation of aquatic biodiversity is critical in mitigating the effects of climate change. Aquatic scene understanding plays a pivotal role in aiding marine scientists in their decision-making processes. In this p…
Object CountingScene UnderstandingA Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches
Object counting has recently shifted towards class-agnostic counting (CAC), which addresses the challenge of counting objects across arbitrary categories, tackling a critical need in versatile counting systems. While hum…
Object CountingMamba-MOC: A Multicategory Remote Object Counting via State Space Model
Multicategory remote object counting is a fundamental task in computer vision, aimed at accurately estimating the number of objects of various categories in remote images. Existing methods rely on CNNs and Transformers, …
MambaObjectObject CountingHierarchical 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+3T2ICount: Enhancing Cross-modal Understanding for Zero-Shot Counting
Zero-shot object counting aims to count instances of arbitrary object categories specified by text descriptions. Existing methods typically rely on vision-language models like CLIP, but often exhibit limited sensitiv…
DenoisingObject CountingSensitivityZero-Shot CountingVision Transformers for Weakly-Supervised Microorganism Enumeration
Microorganism enumeration is an essential task in many applications, such as assessing contamination levels or ensuring health standards when evaluating surface cleanliness. However, it's traditionally performed by human…
Density EstimationInstance SegmentationObject CountingSemantic SegmentationGEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks
While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they fall short in addressing the unique demands of geospatial applications. Generic VLM benchmarks are not designed to handle t…
BenchmarkingObject CountingScene UnderstandingCounting Stacked Objects from Multi-View Images
Visual object counting is a fundamental computer vision task underpinning numerous real-world applications, from cell counting in biomedicine to traffic and wildlife monitoring. However, existing methods struggle to hand…
3D geometryObject CountingEfficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark
The dynamic imbalance of the fore-background is a major challenge in video object counting, which is usually caused by the sparsity of foreground objects. This often leads to severe under- and over-prediction problems an…
Object CountingOptical Flow EstimationRepresentation LearningBoundary Attention Constrained Zero-Shot Layout-To-Image Generation
Recent text-to-image diffusion models excel at generating high-resolution images from text but struggle with precise control over spatial composition and object counting. To address these challenges, several studies deve…
Image GenerationLayout-to-Image GenerationObject Counting