Point Segment and Count: A Generalized Framework for Object Counting
Class-agnostic object counting aims to count all objects in an image with respect to example
boxes or class names aka few-shot and zero-shot counting. In this paper we propose a …
boxes or class names aka few-shot and zero-shot counting. In this paper we propose a …
A novel mechanical fault diagnosis for high-voltage circuit breakers with zero-shot learning
Q Yang, Y Liao - Expert Systems with Applications, 2024 - Elsevier
In recent years, data-driven methods have been widely used in the field of high-voltage
circuit breakers (HVCBs) fault diagnosis. However, due to the complex mechanical structure …
circuit breakers (HVCBs) fault diagnosis. However, due to the complex mechanical structure …
GCNet: Probing self-similarity learning for generalized counting network
The class-agnostic counting (CAC) problem has garnered significant attention recently due
to its broad societal applications and formidable challenges. Existing approaches to …
to its broad societal applications and formidable challenges. Existing approaches to …
Referring Expression Counting
Existing counting tasks are limited to the class level which don't account for fine-grained
details within the class. In real applications it often requires in-context or referring human …
details within the class. In real applications it often requires in-context or referring human …
Vlcounter: Text-aware visual representation for zero-shot object counting
Zero-Shot Object Counting~(ZSOC) aims to count referred instances of arbitrary classes in a
query image without human-annotated exemplars. To deal with ZSOC, preceding studies …
query image without human-annotated exemplars. To deal with ZSOC, preceding studies …
DAVE-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 …
based on only few or no exemplars annotated in the image. The current state-of-the-art …
Counting guidance for high fidelity text-to-image synthesis
Recently, the quality and performance of text-to-image generation significantly advanced
due to the impressive results of diffusion models. However, text-to-image diffusion models …
due to the impressive results of diffusion models. However, text-to-image diffusion models …
Dense object detection methods in RAW UAV imagery based on YOLOv8
Z Wu, X Wang, M Jia, M Liu, C Sun, C Wu, J Wang - Scientific Reports, 2024 - nature.com
Accurate, fast and lightweight dense target detection methods are highly important for
precision agriculture. To detect dense apricot flowers using drones, we propose an …
precision agriculture. To detect dense apricot flowers using drones, we propose an …
Towards zero-shot object counting via deep spatial prior cross-modality fusion
Existing counting models predominantly operate on a specific category of objects, such as
crowds and vehicles. The recent emergence of multi-modal foundational models, eg …
crowds and vehicles. The recent emergence of multi-modal foundational models, eg …
MoPE: Parameter-Efficient and Scalable Multimodal Fusion via Mixture of Prompt Experts
R Jiang, L Liu, C Chen - arXiv preprint arXiv:2403.10568, 2024 - arxiv.org
Prompt-tuning has demonstrated parameter-efficiency in fusing unimodal foundation models
for multimodal tasks. However, its limited adaptivity and expressiveness lead to suboptimal …
for multimodal tasks. However, its limited adaptivity and expressiveness lead to suboptimal …