Vineeth N Balasubramanian

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

Achievements

+10 more ↓

🌍 Conference Polyglot (9) 🏃 Academic Marathon (11) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird

🗺️ Taxonomy Completionist (69) 🌍 Conference Polyglot (9) 🏃 Academic Marathon (11) 🗃️ Keyword Collector (167) ⚡ Prolific Year (16) 🚀 Conference Pioneer 💎 Century Club (46) 🔥 Unstoppable (8) 📈 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