← Authors

Vineeth N Balasubramanian

46 papers · 2015–2026 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (69) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (11) πŸ—ƒοΈ Keyword Collector (167) ⚑ Prolific Year (16) πŸš€ Conference Pioneer πŸ’Ž Century Club (46) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter ❓ The Questioner (4)

Conferences

WACV (12) CVPR (8) AAAI (7) ECCV (6) NIPS (6) ICCV (2) ICML (2) IJCAI (2) ACML (1)

Top co-authors

K J Joseph (6) Anirban Sarkar (5) C.V. Jawahar (5) Abbavaram Gowtham Reddy (5) Anbumani Subramanian (4) Anindya Sarkar (4) Balaji Krishnamurthy (4) Mayank Singh (3) Puneet Mangla (3) Fahad Shahbaz Khan (3)

Keywords

neural network (7) domain generalization (5) domain adaptation (5) representation learning (4) semantic segmentation (4) adversarial learning (4) incremental learning (4) structural causal model (4) adversarial training (4) causal inference (4) self-supervised learning (4) continual learning (4) image classification (3) object detection (3) zero-shot learning (3) generative model (3) catastrophic forgetting (3) feature attribution (3) few-shot learning (3) transfer learning (3)

Papers

LogicCBMs: Logic-Enhanced Concept-Based Learning WACV 2026
A Unified Latent Schrodinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization CVPR 2025
Precise Event Spotting in Sports Videos: Solving Long-Range Dependency and Class Imbalance CVPR 2025
Improving Unsupervised Domain Adaptation: A Pseudo-Candidate Set Approach ECCV 2024
POET: Prompt Offset Tuning for Continual Human Action Adaptation ECCV 2024
Rethinking Robustness of Model Attributions AAAI 2024
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation AAAI 2024
Towards Learning and Explaining Indirect Causal Effects in Neural Networks AAAI 2024
Detecting and Measuring Confounding Using Causal Mechanism Shifts NIPS 2024
Mitigating the Effect of Incidental Correlations on Part-based Learning NIPS 2023
MADG: Margin-based Adversarial Learning for Domain Generalization NIPS 2023
Data-Free Class-Incremental Hand Gesture Recognition ICCV 2023
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach ICCV 2023
Leveraging Test-Time Consensus Prediction for Robustness Against Unseen Noise WACV 2022
On Causally Disentangled Representations AAAI 2022
Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract) AAAI 2022
A Framework for Learning Ante-Hoc Explainable Models via Concepts CVPR 2022
Proto2Proto: Can You Recognize the Car, the Way I Do? CVPR 2022
Unseen Classes at a Later Time? No Problem CVPR 2022
Energy-Based Latent Aligner for Incremental Learning CVPR 2022
Distilling the Undistillable: Learning from a Nasty Teacher ECCV 2022
Novel Class Discovery without Forgetting ECCV 2022
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer ECCV 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors ICML 2022
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals WACV 2022
COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains WACV 2022
FLUID: Few-Shot Self-Supervised Image Deraining WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation WACV 2022
To Miss-Attend Is to Misalign! Residual Self-Attentive Feature Alignment for Adapting Object Detectors WACV 2022
Enhanced Regularizers for Attributional Robustness AAAI 2021
Towards Open World Object Detection CVPR 2021
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-Shot Learning WACV 2021
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach NIPS 2021
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization AAAI 2021
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks NIPS 2021
A Multi-Space Approach to Zero-Shot Object Detection WACV 2020
A Little Fog for a Large Turn WACV 2020
Attributional Robustness Training using Input-Gradient Spatial Alignment ECCV 2020
Munich to Dubai: How far is it for Semantic Segmentation? WACV 2020
Meta-Consolidation for Continual Learning NIPS 2020
Charting the Right Manifold: Manifold Mixup for Few-shot Learning WACV 2020
Neural Network Attributions: A Causal Perspective ICML 2019
Zero-Shot Task Transfer CVPR 2019
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models IJCAI 2019
Submodular Batch Selection for Training Deep Neural Networks IJCAI 2019
Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models ACML 2015