13 papers with code • 1 benchmarks • 1 datasets
These leaderboards are used to track progress in Person Retrieval
Most implemented papers
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
RPP re-assigns these outliers to the parts they are closest to, resulting in refined parts with enhanced within-part consistency.
Dual-Path Convolutional Image-Text Embeddings with Instance Loss
In this paper, we propose a new system to discriminatively embed the image and text to a shared visual-textual space.
Generalizing A Person Retrieval Model Hetero- and Homogeneously
Person re-identification (re-ID) poses unique challenges for unsupervised domain adaptation (UDA) in that classes in the source and target sets (domains) are entirely different and that image variations are largely caused by cameras.
Person Retrieval in Surveillance Video using Height, Color and Gender
A person is commonly described by attributes like height, build, cloth color, cloth type, and gender.
PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description
Instead of using an image query, in this paper, we study the problem of person retrieval in video surveillance with a semantic description.
APES: Audiovisual Person Search in Untrimmed Video
To showcase the potential of our new dataset, we propose an audiovisual baseline and benchmark for person retrieval.
HAT: Hierarchical Aggregation Transformers for Person Re-identification
In this work, we take advantages of both CNNs and Transformers, and propose a novel learning framework named Hierarchical Aggregation Transformer (HAT) for image-based person Re-ID with high performance.
DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval
Many previous methods on text-based person retrieval tasks are devoted to learning a latent common space mapping, with the purpose of extracting modality-invariant features from both visual and textual modality.
Part-based Pseudo Label Refinement for Unsupervised Person Re-identification
In this paper, we propose a novel Part-based Pseudo Label Refinement (PPLR) framework that reduces the label noise by employing the complementary relationship between global and part features.
Cross-Camera Trajectories Help Person Retrieval in a Camera Network
To address this issue, we propose a pedestrian retrieval framework based on cross-camera trajectory generation, which integrates both temporal and spatial information.