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Found 14 papers, 5 papers with code
Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography
To further explore the risk in AD systems and the transferability of practical threats, we propose to leverage typographic attacks against AD systems relying on the decision-making capabilities of Vision-LLMs.
StyleCity: Large-Scale 3D Urban Scenes Stylization
We then optimize the scene style globally by adapting the scale of the style image with the scale of the training views.
Vision-Aware Text Features in Referring Image Segmentation: From Object Understanding to Context Understanding
The complexity of this task increases with the intricacy of the sentences provided.
Ranked #1 on
Referring Expression Segmentation
on RefCOCOg-val
(mIoU metric)
Exploring Boundary of GPT-4V on Marine Analysis: A Preliminary Case Study
In this study, we carry out the preliminary and comprehensive case study of utilizing GPT-4V for marine analysis.
Leveraging Open-Vocabulary Diffusion to Camouflaged Instance Segmentation
Such cross-domain representations are desirable in segmenting camouflaged objects where visual cues are subtle to distinguish the objects from the background, especially in segmenting novel objects which are not seen in training.
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV).
Ranked #1 on
Semantic Segmentation
on LaRS
Test-Time Augmentation for 3D Point Cloud Classification and Segmentation
We are inspired by the recent revolution of learning implicit representation and point cloud upsampling, which can produce high-quality 3D surface reconstruction and proximity-to-surface, respectively.
MarineGPT: Unlocking Secrets of Ocean to the Public
Large language models (LLMs), such as ChatGPT/GPT-4, have proven to be powerful tools in promoting the user experience as an AI assistant.
MarineVRS: Marine Video Retrieval System with Explainability via Semantic Understanding
Building a video retrieval system that is robust and reliable, especially for the marine environment, is a challenging task due to several factors such as dealing with massive amounts of dense and repetitive data, occlusion, blurriness, low lighting conditions, and abstract queries.
Anomaly Detection Using One-Class SVM for Logs of Juniper Router Devices
In this work, we present a new way to get important features from log data of Juniper router devices and use machine learning method (basing on One-Class SVM model) for anomaly detection.
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection.
Marine Video Kit: A New Marine Video Dataset for Content-based Analysis and Retrieval
It is important to remember that domain specific data may be noisier (e. g., endoscopic or underwater videos) and often require more experienced users for effective search.
Ranked #1 on
Retrieval
on MVK
Time-of-Day Neural Style Transfer for Architectural Photographs
Architectural photography is a genre of photography that focuses on capturing a building or structure in the foreground with dramatic lighting in the background.
RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal Features
The key insight is simultaneously performing both tasks via learning of spatial and temporal features from a sequence of point clouds can leverage individual tasks, leading to improved overall performance.
Ranked #1 on
3D Human Reconstruction
on Dynamic FAUST
