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Found 8 papers, 1 papers with code
InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models
The application of large language models (LLMs) has achieved remarkable success in various fields, but their effectiveness in specialized domains like the Chinese insurance industry remains underexplored.
Mitigating Interpretation Bias in Rock Records with Large Language Models: Insights from Paleoenvironmental Analysis
The reconstruction of Earth's history faces significant challenges due to the nonunique interpretations often derived from rock records.
Hyperbolic Learning with Synthetic Captions for Open-World Detection
Specifically, we bootstrap dense synthetic captions using pre-trained VLMs to provide rich descriptions on different regions in images, and incorporate these captions to train a novel detector that generalizes to novel concepts.
MeMOT: Multi-Object Tracking with Memory
We propose an online tracking algorithm that performs the object detection and data association under a common framework, capable of linking objects after a long time span.
ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot
One-stage long-tailed recognition methods improve the overall performance in a "seesaw" manner, i. e., either sacrifice the head's accuracy for better tail classification or elevate the head's accuracy even higher but ignore the tail.
Ranked #19 on
Long-tail Learning
on CIFAR-10-LT (ρ=100)
NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR.
Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model
In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT) of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based camera link model (TCLM).
IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency
Meanwhile, the spatial attention, which focuses on the foreground within the bounding boxes, is generated from the given instance masks and applied to the extracted embedding features.
