175 citations · 219 across the 6 of their papers we have counts for
8 papers
OW-DETR: Open-world Detection Transformer
Akshita Gupta, Sanath Narayan, K J Joseph +3
Open-world object detection (OWOD) is a challenging computer vision problem, where the task is to detect a known set of object categories while simultaneously identifying unknown o…
Discriminative Region-based Multi-Label Zero-Shot Learning
Sanath Narayan, Akshita Gupta, Salman Khan +3
Multi-label zero-shot learning (ZSL) is a more realistic counter-part of standard single-label ZSL since several objects can co-exist in a natural image. However, the occurrence of…
Generative Multi-Label Zero-Shot Learning
Akshita Gupta, Sanath Narayan, Salman Khan +3
Multi-label zero-shot learning strives to classify images into multiple unseen categories for which no data is available during training. The test samples can additionally contain…
Safety Verification of Model Based Reinforcement Learning Controllers
Akshita Gupta, Inseok Hwang
Model-based reinforcement learning (RL) has emerged as a promising tool for developing controllers for real world systems (e.g., robotics, autonomous driving, etc.). However, real…
Safety-guaranteed Reinforcement Learning based on Multi-class Support Vector Machine
Kwangyeon Kim, Akshita Gupta, Hong-Cheol Choi +1
Several works have addressed the problem of incorporating constraints in the reinforcement learning (RL) framework, however majority of them can only guarantee the satisfaction of…
Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
Sanath Narayan, Akshita Gupta, Fahad Shahbaz Khan +2
Zero-shot learning strives to classify unseen categories for which no data is available during training. In the generalized variant, the test samples can further belong to seen or…
iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
Syed Waqas Zamir, Aditya Arora, Akshita Gupta +7
Existing Earth Vision datasets are either suitable for semantic segmentation or object detection. In this work, we introduce the first benchmark dataset for instance segmentation i…
Acoustic Features Fusion using Attentive Multi-channel Deep Architecture
Gaurav Bhatt, Akshita Gupta, Aditya Arora +1
In this paper, we present a novel deep fusion architecture for audio classification tasks. The multi-channel model presented is formed using deep convolution layers where different…