Clip-count: Towards text-guided zero-shot object counting
Recent advances in visual-language models have shown remarkable zero-shot text-image
matching ability that is transferable to downstream tasks such as object detection and …
matching ability that is transferable to downstream tasks such as object detection and …
Lmc: Large model collaboration with cross-assessment for training-free open-set object recognition
Open-set object recognition aims to identify if an object is from a class that has been
encountered during training or not. To perform open-set object recognition accurately, a key …
encountered during training or not. To perform open-set object recognition accurately, a key …
CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning
L Chen, X Wang, J Lu, S Lin… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract 3D Scene Graph Generation (3DSGG) aims to classify objects and their predicates
within 3D point cloud scenes. However current 3DSGG methods struggle with two main …
within 3D point cloud scenes. However current 3DSGG methods struggle with two main …
Learning to Count without Annotations
While recent supervised methods for reference-based object counting continue to improve
the performance on benchmark datasets they have to rely on small datasets due to the cost …
the performance on benchmark datasets they have to rely on small datasets due to the cost …
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 …
Efficient Crowd Counting via Dual Knowledge Distillation
Most researchers focus on designing accurate crowd counting models with heavy
parameters and computations but ignore the resource burden during the model deployment …
parameters and computations but ignore the resource burden during the model deployment …
Unlabeled scene adaptive crowd counting via meta-ensemble learning
The objective of unlabeled scene adaptive crowd counting (USACC) is to adapt the crowd
counting model to a particular scene by utilizing only a handful of unlabeled images from …
counting model to a particular scene by utilizing only a handful of unlabeled images from …
[HTML][HTML] Cross-scale vision transformer for crowd localization
Crowd localization can provide the positions of individuals and the total number of people,
which has great application value for security monitoring and public management …
which has great application value for security monitoring and public management …
Enhancing Zero-shot Counting via Language-guided Exemplar Learning
Recently, Class-Agnostic Counting (CAC) problem has garnered increasing attention owing
to its intriguing generality and superior efficiency compared to Category-Specific Counting …
to its intriguing generality and superior efficiency compared to Category-Specific Counting …
Hierarchical Kernel Interaction Network for Remote Sensing Object Counting
Different from object counting in surveillance scenes, remote sensing object counting
encounters knotty challenges due to its tiny scale and cluttered background. However …
encounters knotty challenges due to its tiny scale and cluttered background. However …