Search Results for author:
Found 9 papers, 4 papers with code
Improving Generalization for AI-Synthesized Voice Detection
AI-synthesized voice technology has the potential to create realistic human voices for beneficial applications, but it can also be misused for malicious purposes.
PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference
To solve this, we first introduce a novel property of lightweight ConvNets: their ability to identify key discriminative patch regions in images, irrespective of model's final accuracy or size.
Detecting Multimedia Generated by Large AI Models: A Survey
The rapid advancement of Large AI Models (LAIMs), particularly diffusion models and large language models, has marked a new era where AI-generated multimedia is increasingly integrated into various aspects of daily life.
Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection
We propose an embarrassingly simple method -- instance-aware repeat factor sampling (IRFS) to address the problem of imbalanced data in long-tailed object detection.
Object Detection for Autonomous Dozers
We introduce a new type of autonomous vehicle - an autonomous dozer that is expected to complete construction site tasks in an efficient, robust, and safe manner.
PseudoProp: Robust Pseudo-Label Generation for Semi-Supervised Object Detection in Autonomous Driving Systems
Semi-supervised object detection methods are widely used in autonomous driving systems, where only a fraction of objects are labeled.
Movies2Scenes: Using Movie Metadata to Learn Scene Representation
However, labeling individual scenes is a time-consuming process.
Complement Objective Training
Although being a widely-adopted approach, using cross entropy as the primary objective exploits mostly the information from the ground-truth class for maximizing data likelihood, and largely ignores information from the complement (incorrect) classes.
MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning
Recent studies on neural architecture search have shown that automatically designed neural networks perform as good as expert-crafted architectures.
