Object Counting
10개 벤치마크 · 논문 214편 · 이 태스크의 논문 보기 →
Benchmarks
FSC147
CARPK
COCO count-test
TallyQA-Complex
TallyQA-Simple
HowMany-QA
PASCAL VOC
Omnicount-191
TRANCOS
Most implemented
YOLO9000: Better, Faster, Stronger
You Only Look Once: Unified, Real-Time Object Detection
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
Synbols: Probing Learning Algorithms with Synthetic Datasets
Papers
Counting Beyond Instances: A Benchmark for Group-Individual Object Counting
Visual counting is commonly formulated at the instance level, aiming to estimate how many objects of a queried category appear in an image. However, real-world counting often involves higher-level semantic units formed b…
Object CountingDepth-Guided Video Object Counting in Crowded Scenes
Our primary objective is to advance video object counting in crowded scenes, aiming to robustly count all instances of a target category based on given text or visual prompts. Existing methods rely on RGB information, li…
Object CountingSpatially-Aware Class-Agnostic Object Counting
Generalised object counting aims to estimate the number of instances of an arbitrary object category from a single image, but many recent methods can struggle on structurally complex objects due to limited spatial modell…
Object CountingThe Count Is There, but Misaligned: Understanding and Correcting Counting Failures in VLMs
Despite strong performance on many multimodal tasks, vision-language models (VLMs) still struggle with basic object counting. We investigate whether this reflects missing internal knowledge or a gap between internal repr…
Object CountingAdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting
Zero-shot object counting (ZOC) aims to count instances of arbitrary object categories specified only through textual prompts. Recent training-free approaches leverage foundation models such as SAM to reformulate countin…
Object CountingCan AI Draw Science? A Benchmark for Evaluating Scientific Figure Generation by Text-to-Image and Multimodal Models
Text-to-image and multimodal generative models are increasingly used to produce scientific figures such as mechanism diagrams, experimental-design schematics, conceptual frameworks, and graphical abstracts. Yet existing …
Object Counting