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Found 14 papers, 4 papers with code
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred to as open-vocabulary semantic segmentation (OVS).
Knowledge Distillation
Open Vocabulary Semantic Segmentation
+3
Point-Syn2Real: Semi-Supervised Synthetic-to-Real Cross-Domain Learning for Object Classification in 3D Point Clouds
Object classification using LiDAR 3D point cloud data is critical for modern applications such as autonomous driving.
Improved Feature Distillation via Projector Ensemble
Motivated by the positive effect of the projector in feature distillation, we propose an ensemble of projectors to further improve the quality of student features.
InvisibiliTee: Angle-agnostic Cloaking from Person-Tracking Systems with a Tee
After a survey for person-tracking system-induced privacy concerns, we propose a black-box adversarial attack method on state-of-the-art human detection models called InvisibiliTee.
STAR-GNN: Spatial-Temporal Video Representation for Content-based Retrieval
It models a video with a lattice feature graph in which the nodes represent regions of different granularity, with weighted edges that represent the spatial and temporal links.
A Real-time Edge-AI System for Reef Surveys
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are ongoing to manage COTS populations to ecologically sustainable levels.
Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and GNSS data
However, the multimodal animal behavior classification algorithm based on posterior probability fusion is preferable to the one based on feature concatenation as it delivers better classification accuracy, has less computational and memory complexity, is more robust to sensor data failure, and enjoys better modularity.
Instant Graph Neural Networks for Dynamic Graphs
With the development of numerous GNN variants, recent years have witnessed groundbreaking results in improving the scalability of GNNs to work on static graphs with millions of nodes.
The CSIRO Crown-of-Thorn Starfish Detection Dataset
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are underway in an attempt to manage COTS populations to ecologically sustainable levels.
A novel policy for pre-trained Deep Reinforcement Learning for Speech Emotion Recognition
In addition, extended learning period is a general challenge for deep RL which can impact the speed of learning for SER.
Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN
Such tendency indicates that the model indeed learned how to toy with both image retrieval systems and human eyes.
RUM: network Representation learning throUgh Multi-level structural information preservation
We propose a novel network representations learning model framework called RUM (network Representation learning throUgh Multi-level structural information preservation).
Learning in High-Dimensional Multimedia Data: The State of the Art
Given the high dimensionality and the high complexity of multimedia data, it is important to investigate new machine learning algorithms to facilitate multimedia data analysis.
Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
The prediction of periodical time-series remains challenging due to various types of data distortions and misalignments.
