3 citations · 3 across the 8 of their papers we have counts for
8 papers
DynaTokens: Controlling Token Dynamics for Continual Video-Language Understanding
Toan Nguyen, Yang Liu, Celso De Melo +1
Continual VideoQA with multimodal LLMs remains challenging because sequential adaptation induces task interference, while storing task-specific prompts becomes impractical as task…
Texture- and Shape-based Adversarial Attacks for Overhead Image Vehicle Detection
Mikael Yeghiazaryan, Sai Abhishek Siddhartha Namburu, Emily Kim +4
Detecting vehicles in aerial images is difficult due to complex backgrounds, small object sizes, shadows, and occlusions. Although recent deep learning advancements have improved o…
A Mamba-based Siamese Network for Remote Sensing Change Detection
Jay N. Paranjape, Celso de Melo, Vishal M. Patel
Change detection in remote sensing images is an essential tool for analyzing a region at different times. It finds varied applications in monitoring environmental changes, man-made…
ViLCo-Bench: VIdeo Language COntinual learning Benchmark
Tianqi Tang, Shohreh Deldari, Hao Xue +2
Video language continual learning involves continuously adapting to information from video and text inputs, enhancing a model's ability to handle new tasks while retaining prior kn…
WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather
Blake Gella, Howard Zhang, Rishi Upadhyay +7
We propose a method to infer semantic segmentation maps from images captured under adverse weather conditions. We begin by examining existing models on images degraded by weather c…
Entropic Open-set Active Learning
Bardia Safaei, Vibashan VS, Celso M. de Melo +1
Active Learning (AL) aims to enhance the performance of deep models by selecting the most informative samples for annotation from a pool of unlabeled data. Despite impressive perfo…
Unsupervised Video Domain Adaptation with Masked Pre-Training and Collaborative Self-Training
Arun Reddy, William Paul, Corban Rivera +3
In this work, we tackle the problem of unsupervised domain adaptation (UDA) for video action recognition. Our approach, which we call UNITE, uses an image teacher model to adapt a…
Open-Set Automatic Target Recognition
Bardia Safaei, Vibashan VS, Celso M. de Melo +2
Automatic Target Recognition (ATR) is a category of computer vision algorithms which attempts to recognize targets on data obtained from different sensors. ATR algorithms are exten…