172 citations · 1.2k across the 80 of their papers we have counts for
8 papers · 1 filter
DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier
Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty +1
In this era of digital information explosion, an abundance of data from numerous modalities is being generated as well as archived everyday. However, most problems associated with…
GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions
Jogendra Nath Kundu, Maharshi Gor, Dakshit Agrawal +1
Despite the remarkable success of generative adversarial networks, their performance seems less impressive for diverse training sets, requiring learning of discontinuous mapping fu…
UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation
Jogendra Nath Kundu, Nishank Lakkakula, R. Venkatesh Babu
Aiming towards human-level generalization, there is a need to explore adaptable representation learning methods with greater transferability. Most existing approaches independently…
FDA: Feature Disruptive Attack
Aditya Ganeshan, B. S. Vivek, R. Venkatesh Babu
Though Deep Neural Networks (DNN) show excellent performance across various computer vision tasks, several works show their vulnerability to adversarial samples, i.e., image sample…
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
Deepak Babu Sam, Skand Vishwanath Peri, Mukuntha Narayanan Sundararaman +2
We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm. Typical counting models predict crowd density for…
Enhancing Salient Object Segmentation Through Attention
Anuj Pahuja, Avishek Majumder, Anirban Chakraborty +1
Segmenting salient objects in an image is an important vision task with ubiquitous applications. The problem becomes more challenging in the presence of a cluttered and textured ba…
Zero-Shot Knowledge Distillation in Deep Networks
Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj +2
Knowledge distillation deals with the problem of training a smaller model (Student) from a high capacity source model (Teacher) so as to retain most of its performance. Existing ap…
Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network
Priyanka Mandikal, R. Venkatesh Babu
Reconstructing a high-resolution 3D model of an object is a challenging task in computer vision. Designing scalable and light-weight architectures is crucial while addressing this…