7 citations · 14 across the 23 of their papers we have counts for
9 papers · 1 filter
SmoothOperator: Enhancing Representations for Fine-grained Open-set Recognition via Modulated Label Smoothing
Thiru Thillai Nadarasar Bahavan, Yu Xia, Sachith Seneviratne +1
Open Set Recognition (OSR) aims to enable models to accurately classify known classes while rejecting samples from unseen classes. A key challenge in OSR lies in the inability to m…
FedLAS: Feature-Modulated Bidirectional Label Smoothing for Neural Network Calibration
Thiru Thillai Nadarasar Bahavan, Sachith Seneviratne, Saman Halgamuge
Deep Neural Network (DNN) classifiers suffer from poor calibration when their softmax outputs (predictive confidence) deviate from the empirical likelihoods. This manifests itself…
Parameter-efficient Prompt Tuning and Hierarchical Textual Guidance for Few-shot Whole Slide Image Classification
Jayanie Bogahawatte, Sachith Seneviratne, Saman Halgamuge
Whole Slide Images (WSIs) are giga-pixel in scale and are typically partitioned into small instances in WSI classification pipelines for computational feasibility. However, obtaini…
MSRAMIE: Multimodal Structured Reasoning Agent for Multi-instruction Image Editing
Zhaoyuan Qiu, Ken Chen, Xiangwei Wang +3
Existing instruction-based image editing models perform well with simple, single-step instructions but degrade in realistic scenarios that involve multiple, lengthy, and interdepen…
Beyond Deepfake vs Real: Facial Deepfake Detection in the Open-Set Paradigm
Nadarasar Bahavan, Sachith Seneviratne, Sanjay Saha +3
Facial forgery methods such as deepfakes can be misused for identity manipulation and spreading misinformation. They have evolved alongside advancements in generative AI, leading t…
SphOR: A Representation Learning Perspective on Open-set Recognition for Identifying Unknown Classes in Deep Learning Models
Nadarasar Bahavan, Sachith Seneviratne, Saman Halgamuge
The reliance on Deep Neural Network (DNN)-based classifiers in safety-critical and real-world applications necessitates Open-Set Recognition (OSR). OSR enables the identification o…
TT-MPD: Test Time Model Pruning and Distillation
Haihang Wu, Wei Wang, Tamasha Malepathirana +3
Pruning can be an effective method of compressing large pre-trained models for inference speed acceleration. Previous pruning approaches rely on access to the original training dat…
AniFaceDiff: Animating Stylized Avatars via Parametric Conditioned Diffusion Models
Ken Chen, Sachith Seneviratne, Wei Wang +7
Animating stylized avatars with dynamic poses and expressions has attracted increasing attention for its broad range of applications. Previous research has made significant progres…
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning
Tamasha Malepathirana, Damith Senanayake, Saman Halgamuge
Catastrophic forgetting; the loss of old knowledge upon acquiring new knowledge, is a pitfall faced by deep neural networks in real-world applications. Many prevailing solutions to…