Search Results for author:
Found 6 papers, 4 papers with code
Enhanced Training of Query-Based Object Detection via Selective Query Recollection
This paper investigates a phenomenon where query-based object detectors mispredict at the last decoding stage while predicting correctly at an intermediate stage.
Ranked #10 on
Object Detection
on COCO 2017 val
Unitail: Detecting, Reading, and Matching in Retail Scene
To make full use of computer vision technology in stores, it is required to consider the actual needs that fit the characteristics of the retail scene.
Ranked #1 on
Dense Object Detection
on SKU-110K
Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
In this work, we investigate utilizing this semantic relation together with the visual information and introduce explicit relation reasoning into the learning of novel object detection.
Ranked #14 on
Few-Shot Object Detection
on MS-COCO (30-shot)
Solving Missing-Annotation Object Detection with Background Recalibration Loss
In this paper, we introduce a superior solution called Background Recalibration Loss (BRL) that can automatically re-calibrate the loss signals according to the pre-defined IoU threshold and input image.
Soft Anchor-Point Object Detection
In this work, we boost the performance of the anchor-point detector over the key-point counterparts while maintaining the speed advantage.
Ranked #3 on
Dense Object Detection
on SKU-110K
SAPD：Soft Anchor-Point Detector
In this work, we aim at finding a new balance of speed and accuracy for anchor-free detectors.
