Towards effective person search with deep learning: A survey from systematic perspective
Person search detects and retrieves simultaneously a query person across uncropped
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
Feature fusion vision transformer for fine-grained visual categorization
The core for tackling the fine-grained visual categorization (FGVC) is to learn subtle yet
discriminative features. Most previous works achieve this by explicitly selecting the …
discriminative features. Most previous works achieve this by explicitly selecting the …
Joint discriminative representation learning for end-to-end person search
Person search simultaneously detects and retrieves a query person from uncropped scene
images. Existing methods are either two-step or end-to-end. The former employs two …
images. Existing methods are either two-step or end-to-end. The former employs two …
Learning consistent region features for lifelong person re-identification
The lifelong person re-identification (LRe-ID) model retrieves a person across multiple
cameras in continuous data streams and learns new coming datasets incrementally …
cameras in continuous data streams and learns new coming datasets incrementally …
Mix-ViT: Mixing attentive vision transformer for ultra-fine-grained visual categorization
Ultra-fine-grained visual categorization (ultra-FGVC) moves down the taxonomy level to
classify sub-granularity categories of fine-grained objects. This inevitably poses a challenge …
classify sub-granularity categories of fine-grained objects. This inevitably poses a challenge …
SPARE: Self-supervised part erasing for ultra-fine-grained visual categorization
This paper presents SPARE, a self-supervised part erasing framework for ultra-fine-grained
visual categorization. The key insight of our model is to learn discriminative representations …
visual categorization. The key insight of our model is to learn discriminative representations …
Ssfe-net: Self-supervised feature enhancement for ultra-fine-grained few-shot class incremental learning
Abstract Ultra-Fine-Grained Visual Categorization (ultra-FGVC) has become a popular
problem due to its great real-world potential for classifying the same or closely related …
problem due to its great real-world potential for classifying the same or closely related …
Dynamic and static mutual fitting for action recognition
Action recognition is intended to classify a video into a certain category by aggregating and
summarizing its temporal and spatial information. Existing methods have achieved …
summarizing its temporal and spatial information. Existing methods have achieved …
Towards generalizable person re-identification with a bi-stream generative model
Generalizable person re-identification (re-ID) has attracted growing attention due to its
powerful adaptation capability in the unseen data domain. However, existing solutions often …
powerful adaptation capability in the unseen data domain. However, existing solutions often …
A Lie algebra representation for efficient 2D shape classification
Riemannian manifold plays a vital role as a powerful mathematical tool in computer vision,
with important applications in curved shape analysis and classification. Significant progress …
with important applications in curved shape analysis and classification. Significant progress …