Search Results for author:
Found 13 papers, 5 papers with code
GaitFormer: Revisiting Intrinsic Periodicity for Gait Recognition
The second component is the Temporal Aggregation Module (TAM), which separates embeddings into trend and seasonal components, and extracts meaningful temporal correlations to identify primary components, while filtering out random noise.
Style Variable and Irrelevant Learning for Generalizable Person Re-identification
In this paper, we first verify through an experiment that style factors are a vital part of domain bias.
Domain Generalization
Generalizable Person Re-identification
+1
Motion Sensitive Contrastive Learning for Self-supervised Video Representation
Contrastive learning has shown great potential in video representation learning.
Tracking Objects as Pixel-wise Distributions
During inference, a pixel-wise association procedure is proposed to recover object connections through frames based on the pixel-wise prediction.
Symmetric Network with Spatial Relationship Modeling for Natural Language-based Vehicle Retrieval
Natural language (NL) based vehicle retrieval aims to search specific vehicle given text description.
Improving Human-Object Interaction Detection via Phrase Learning and Label Composition
Human-Object Interaction (HOI) detection is a fundamental task in high-level human-centric scene understanding.
Learning Context-Aware Embedding for Person Search
Person Search is a relevant task that aims to jointly solve Person Detection and Person Re-identification(re-ID).
Efficient DETR: Improving End-to-End Object Detector with Dense Prior
By taking advantage of both dense detection and sparse set detection, Efficient DETR leverages dense prior to initialize the object containers and brings the gap of the 1-decoder structure and 6-decoder structure.
End-to-End Human Object Interaction Detection with HOI Transformer
We propose HOI Transformer to tackle human object interaction (HOI) detection in an end-to-end manner.
Ranked #29 on
Human-Object Interaction Detection
on HICO-DET
(using extra training data)
Double Anchor R-CNN for Human Detection in a Crowd
Double Anchor RPN is developed to capture body and head parts in pairs.
WIDER Face and Pedestrian Challenge 2018: Methods and Results
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian.
CrowdHuman: A Benchmark for Detecting Human in a Crowd
There are a total of $470K$ human instances from the train and validation subsets, and $~22. 6$ persons per image, with various kinds of occlusions in the dataset.
Ranked #7 on
Pedestrian Detection
on Caltech
(using extra training data)
SFace: An Efficient Network for Face Detection in Large Scale Variations
A new dataset called 4K-Face is also introduced to evaluate the performance of face detection with extreme large scale variations.
