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ORCIDVineeth N. Balasubramanian
Vineeth Nallure Balasubramanian – Vineeth Balasubramanian
Person information
- affiliation: Indian Institute of Technology, Hyderabad, Department of Computer Science and Engineering
- affiliation: Arizona State University, Tempe, Department of Computer Science and Engineering
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2020 – today
- 2024
[j13]Thrupthi Ann John
, Vineeth N. Balasubramanian, C. V. Jawahar:
Explaining Deep Face Algorithms Through Visualization: A Survey. IEEE Trans. Biom. Behav. Identity Sci. 6(1): 15-29 (2024)- [c128]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. AAAI 2024: 2688-2696 - [c127]Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation. AAAI 2024: 14793-14801 - [c126]Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin Godfrey L, Varshaneya V, Vineeth N. Balasubramanian, Satyanarayan Kar:
Towards Learning and Explaining Indirect Causal Effects in Neural Networks. AAAI 2024: 14802-14810 - [c125]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Gaurav Sinha:
Interpretable Model Drift Detection. COMAD/CODS 2024: 1-9 - [c124]Tarun Ram Menta, Surgan Jandial, Akash Patil, Saketh Bachu, Vimal K. B., Balaji Krishnamurthy, Vineeth N. Balasubramanian, Mausoom Sarkar, Chirag Agarwal:
Active Transferability Estimation. CVPR Workshops 2024: 2659-2670 - [c123]Aveen Dayal, Rishabh Lalla, Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
Improving Unsupervised Domain Adaptation: A Pseudo-candidate Set Approach. ECCV (32) 2024: 127-144 - [c122]Prachi Garg, K. J. Joseph, Vineeth N. Balasubramanian, Necati Cihan Camgöz, Chengde Wan, Kenrick Kin, Weiguang Si, Shugao Ma, Fernando De la Torre:
POET: Prompt Offset Tuning for Continual Human Action Adaptation. ECCV (64) 2024: 436-455 - [c121]Pranoy Panda, Siddharth Tandon, Vineeth N. Balasubramanian:
FW-Shapley: Real-Time Estimation of Weighted Shapley Values. ICASSP 2024: 6210-6214 - [c120]Sairam VC Rebbapragada, Pranoy Panda, Vineeth N. Balasubramanian:
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks. ICRA 2024: 6627-6633 - [c119]Hiran Sarkar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth N. Balasubramanian:
Open-Set Object Detection By Aligning Known Class Representations. WACV 2024: 218-227 - [c118]Bhat Dittakavi, Bharathi Callepalli, Aleti Vardhan, Sai Vikas Desai, Vineeth N. Balasubramanian:
CARE: Counterfactual-based Algorithmic Recourse for Explainable Pose Correction. WACV 2024: 4890-4899 - [i91]Tanmay Garg, Deepika Vemuri, Vineeth N. Balasubramanian:
Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks. CoRR abs/2401.04647 (2024) - [i90]Purbayan Kar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth Balasubramanian:
Fiducial Focus Augmentation for Facial Landmark Detection. CoRR abs/2402.15044 (2024) - [i89]Sairam VC Rebbapragada, Pranoy Panda, Vineeth N. Balasubramanian:
C2FDrone: Coarse-to-Fine Drone-to-Drone Detection using Vision Transformer Networks. CoRR abs/2404.19276 (2024) - [i88]Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
Can Better Text Semantics in Prompt Tuning Improve VLM Generalization? CoRR abs/2405.07921 (2024) - [i87]Aniket Vashishtha, Abhinav Kumar, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma:
Teaching Transformers Causal Reasoning through Axiomatic Training. CoRR abs/2407.07612 (2024) - [i86]Vishal M. Chudasama, Hiran Sarkar, Pankaj Wasnik, Vineeth N. Balasubramanian, Jayateja Kalla:
Beyond Few-shot Object Detection: A Detailed Survey. CoRR abs/2408.14249 (2024) - [i85]Rahul Ramachandran, Tejal Kulkarni, Charchit Sharma, Deepak Vijaykeerthy, Vineeth N. Balasubramanian:
On Evaluation of Vision Datasets and Models using Human Competency Frameworks. CoRR abs/2409.04041 (2024) - 2023
- [c117]Purbayan Kar, Vishal M. Chudasama, Naoyuki Onoe, Pankaj Wasnik, Vineeth Balasubramanian:
Fiducial Focus Augmentation for Facial Landmark Detection. BMVC 2023: 562-565 - [c116]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Weakly-supervised Spatially Grounded Concept Learner for Few-Shot Learning. BMVC 2023: 858-867 - [c115]Surgan Jandial, Yash Khasbage, Arghya Pal, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning. COMAD/CODS 2023: 10-18 - [c114]Vimal K. B., Saketh Bachu, Tanmay Garg, Niveditha Lakshmi Narasimhan, Raghavan Konuru, Vineeth N. Balasubramanian:
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach. ICCV 2023: 11575-11586 - [c113]Shubhra Aich, Jesús Ruiz-Santaquiteria, Zhenyu Lu, Prachi Garg, K. J. Joseph, Alvaro Fernandez Garcia, Vineeth N. Balasubramanian, Kenrick Kin, Chengde Wan, Necati Cihan Camgöz, Shugao Ma, Fernando De la Torre:
Data-Free Class-Incremental Hand Gesture Recognition. ICCV 2023: 20901-20910 - [c112]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Mitigating the Effect of Incidental Correlations on Part-based Learning. NeurIPS 2023 - [c111]Aveen Dayal, Vimal K. B., Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
MADG: Margin-based Adversarial Learning for Domain Generalization. NeurIPS 2023 - [c110]Rebbapragada V. C. Sairam, Monish Keswani, Uttaran Sinha, Nishit Shah, Vineeth N. Balasubramanian:
ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection. WACV 2023: 3708-3717 - [c109]Gaurav Bhatt, Vineeth N. Balasubramanian:
Learning Style Subspaces for Controllable Unpaired Domain Translation. WACV 2023: 4209-4218 - [i84]Tarun Ram Menta, Surgan Jandial, Akash Patil, Vimal KB, Saketh Bachu, Balaji Krishnamurthy, Vineeth N. Balasubramanian, Chirag Agarwal, Mausoom Sarkar:
Towards Estimating Transferability using Hard Subsets. CoRR abs/2301.06928 (2023) - [i83]Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin L. Godfrey, Vineeth N. Balasubramanian, Varshaneya V, Satya Narayanan Kar:
Learning Causal Attributions in Neural Networks: Beyond Direct Effects. CoRR abs/2303.13850 (2023) - [i82]Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg:
Δ-Networks for Efficient Model Patching. CoRR abs/2303.14772 (2023) - [i81]Abbavaram Gowtham Reddy, Saketh Bachu, Saloni Dash, Charchit Sharma, Amit Sharma, Vineeth N. Balasubramanian:
Rethinking Counterfactual Data Augmentation Under Confounding. CoRR abs/2305.18183 (2023) - [i80]Vimal KB, Saketh Bachu, Tanmay Garg, Niveditha Lakshmi Narasimhan, Raghavan Konuru, Vineeth N. Balasubramanian:
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach. CoRR abs/2309.02429 (2023) - [i79]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Explaining Deep Face Algorithms through Visualization: A Survey. CoRR abs/2309.14715 (2023) - [i78]Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N. Balasubramanian:
Mitigating the Effect of Incidental Correlations on Part-based Learning. CoRR abs/2310.00377 (2023) - [i77]Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma:
Causal Inference Using LLM-Guided Discovery. CoRR abs/2310.15117 (2023) - [i76]Aveen Dayal, Vimal K. B., Linga Reddy Cenkeramaddi, C. Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian:
MADG: Margin-based Adversarial Learning for Domain Generalization. CoRR abs/2311.08503 (2023) - [i75]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. CoRR abs/2312.10534 (2023) - 2022
- [j12]Vineeth N. Balasubramanian:
Toward explainable deep learning. Commun. ACM 65(11): 68-69 (2022) - [j11]K. J. Joseph, Jathushan Rajasegaran, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Incremental Object Detection via Meta-Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9209-9216 (2022) - [c108]Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian:
On Causally Disentangled Representations. AAAI 2022: 8089-8097 - [c107]Arjun Ashok, Chaitanya Devaguptapu, Vineeth N. Balasubramanian:
Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract). AAAI 2022: 12905-12906 - [c106]Piyushi Manupriya, Tarun Ram Menta, Saketha Nath Jagarlapudi, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. AISTATS 2022: 2173-2190 - [c105]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam, Vineeth N. Balasubramanian:
Universalization of Any Adversarial Attack using Very Few Test Examples. COMAD/CODS 2022: 72-80 - [c104]Bhat Dittakavi, Divyagna Bavikadi, Sai Vikas Desai, Soumi Chakraborty, Nishant Reddy, Vineeth N. Balasubramanian, Bharathi Callepalli, Ayon Sharma:
Pose Tutor: An Explainable System for Pose Correction in the Wild. CVPR Workshops 2022: 3539-3548 - [c103]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Spacing Loss for Discovering Novel Categories. CVPR Workshops 2022: 3760-3765 - [c102]K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian:
Energy-based Latent Aligner for Incremental Learning. CVPR 2022: 7442-7451 - [c101]Hari Chandana Kuchibhotla, Sumitra S. Malagi, Shivam Chandhok, Vineeth N. Balasubramanian:
Unseen Classes at a Later Time? No Problem. CVPR 2022: 9235-9244 - [c100]Monish Keswani, Sriranjani Ramakrishnan, Nishant Reddy, Vineeth N. Balasubramanian:
Proto2Proto: Can you recognize the car, the way I do? CVPR 2022: 10223-10233 - [c99]Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar, Vineeth N. Balasubramanian:
A Framework for Learning Ante-hoc Explainable Models via Concepts. CVPR 2022: 10276-10285 - [c98]Arjun Ashok, K. J. Joseph, Vineeth N. Balasubramanian:
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer. ECCV (27) 2022: 105-122 - [c97]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Novel Class Discovery Without Forgetting. ECCV (24) 2022: 570-586 - [c96]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. ECCV (13) 2022: 587-603 - [c95]Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma:
Matching Learned Causal Effects of Neural Networks with Domain Priors. ICML 2022: 10676-10696 - [c94]Deepak Kumar Singh, Shyam Nandan Rai, K. J. Joseph, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
New Objects on the Road? No Problem, We'll Learn Them Too. IROS 2022: 1972-1978 - [c93]Thrupthi Ann John, Isha Dua, Vineeth N. Balasubramanian, C. V. Jawahar:
ETL: Efficient Transfer Learning for Face Tasks. VISIGRAPP (5: VISAPP) 2022: 248-257 - [c92]Vaishnavi Khindkar, Chetan Arora, Vineeth N. Balasubramanian, Anbumani Subramanian, Rohit Saluja, C. V. Jawahar:
To miss-attend is to misalign! Residual Self-Attentive Feature Alignment for Adapting Object Detectors. WACV 2022: 376-386 - [c91]Shyam Nandan Rai, Rohit Saluja, Chetan Arora, Vineeth N. Balasubramanian, Anbumani Subramanian, C. V. Jawahar:
FLUID: Few-Shot Self-Supervised Image Deraining. WACV 2022: 418-427 - [c90]Puneet Mangla, Shivam Chandhok, Vineeth N. Balasubramanian, Fahad Shahbaz Khan:
COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains. WACV 2022: 1618-1627 - [c89]Prachi Garg, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
Multi-Domain Incremental Learning for Semantic Segmentation. WACV 2022: 2080-2090 - [c88]Puneet Mangla, Nupur Kumari, Mayank Singh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
Data InStance Prior (DISP) in Generative Adversarial Networks. WACV 2022: 3471-3481 - [c87]Anindya Sarkar, Anirban Sarkar, Vineeth N. Balasubramanian:
Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise. WACV 2022: 3564-3573 - [c86]Saloni Dash, Vineeth N. Balasubramanian, Amit Sharma:
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals. WACV 2022: 3879-3888 - [e2]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India. Proceedings of Machine Learning Research 189, PMLR 2022 [contents] - [i74]K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian:
Energy-based Latent Aligner for Incremental Learning. CoRR abs/2203.14952 (2022) - [i73]Hari Chandana Kuchibhotla, Sumitra S. Malagi, Shivam Chandhok, Vineeth N. Balasubramanian:
Unseen Classes at a Later Time? No Problem. CoRR abs/2203.16517 (2022) - [i72]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Spacing Loss for Discovering Novel Categories. CoRR abs/2204.10595 (2022) - [i71]Monish Keswani, Sriranjani Ramakrishnan, Nishant Reddy, Vineeth N. Balasubramanian:
Proto2Proto: Can you recognize the car, the way I do? CoRR abs/2204.11830 (2022) - [i70]Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models. CoRR abs/2205.03859 (2022) - [i69]Puneet Mangla, Shivam Chandhok, Milan Aggarwal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
INDIGO: Intrinsic Multimodality for Domain Generalization. CoRR abs/2206.05912 (2022) - [i68]K. J. Joseph, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N. Balasubramanian:
Novel Class Discovery without Forgetting. CoRR abs/2207.10659 (2022) - [i67]Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian:
Learning Modular Structures That Generalize Out-of-Distribution. CoRR abs/2208.03753 (2022) - [i66]Arjun Ashok, K. J. Joseph, Vineeth Balasubramanian:
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer. CoRR abs/2208.03767 (2022) - [i65]Rebbapragada V. C. Sairam, Monish Keswani, Uttaran Sinha, Nishit Shah, Vineeth N. Balasubramanian:
ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection. CoRR abs/2210.04574 (2022) - [i64]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. CoRR abs/2210.11728 (2022) - [i63]Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian:
Counterfactual Generation Under Confounding. CoRR abs/2210.12368 (2022) - [i62]Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian:
Estimating Treatment Effects using Neurosymbolic Program Synthesis. CoRR abs/2211.04370 (2022) - [i61]Amlan Jyoti, Karthik Balaji Ganesh, Manoj Gayala, Nandita Lakshmi Tunuguntla, Sandesh Kamath, Vineeth N. Balasubramanian:
On the Robustness of Explanations of Deep Neural Network Models: A Survey. CoRR abs/2211.04780 (2022) - 2021
- [j10]Puneet Mangla, Vedant Singh, Shreyas Jayant Havaldar, Vineeth Balasubramanian:
On the benefits of defining vicinal distributions in latent space. Pattern Recognit. Lett. 152: 382-390 (2021) - [j9]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Canonical Saliency Maps: Decoding Deep Face Models. IEEE Trans. Biom. Behav. Identity Sci. 3(4): 561-572 (2021) - [c85]Anindya Sarkar, Anirban Sarkar, Vineeth N. Balasubramanian:
Enhanced Regularizers for Attributional Robustness. AAAI 2021: 2532-2540 - [c84]Adepu Ravi Sankar, Yash Khasbage, Rahul Vigneswaran, Vineeth N. Balasubramanian:
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization. AAAI 2021: 9481-9488 - [c83]Shivam Chandhok, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Vineeth N. Balasubramanian, Fahad Shahbaz Khan, Ling Shao:
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains. BMVC 2021: 207 - [c82]Aditya Bharti, Vineeth Nallure Balasubramanian, C. V. Jawahar:
Towards Label-Free Few-Shot Learning: How Far Can We Go? CVIP (1) 2021: 256-268 - [c81]Radhika Dua, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Beyond VQA: Generating Multi-Word Answers and Rationales to Visual Questions. CVPR Workshops 2021: 1623-1632 - [c80]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Instance-Wise Causal Feature Selection for Model Interpretation. CVPR Workshops 2021: 1756-1759 - [c79]K. J. Joseph, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Towards Open World Object Detection. CVPR 2021: 5830-5840 - [c78]Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Pulkit Gopalani, Vineeth N. Balasubramanian:
On Adversarial Robustness: A Neural Architecture Search perspective. ICCVW 2021: 152-161 - [c77]Varshaneya V, S. Balasubramanian, Vineeth Balasubramanian:
Teaching GANs to sketch in vector format. ICVGIP 2021: 1:1-1:8 - [c76]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature generation for long-tail classification. ICVGIP 2021: 41:1-41:9 - [c75]Anindya Sarkar, Anirban Sarkar, Sowrya Gali, Vineeth N. Balasubramanian:
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach. NeurIPS 2021: 12836-12848 - [c74]Sandesh Kamath, Amit Deshpande, Subrahmanyam Kambhampati Venkata, Vineeth N. Balasubramanian:
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks. NeurIPS 2021: 27462-27474 - [c73]Vaasudev Narayanan, Aniket Anand Deshmukh, Ürün Dogan, Vineeth N. Balasubramanian:
On Challenges in Unsupervised Domain Generalization. Pre-Registration Workshop @ NeurIPS 2021: 42-58 - [c72]Shivam Chandhok, Vineeth N. Balasubramanian:
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning. WACV 2021: 3099-3107 - [e1]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Proceedings of Machine Learning Research 157, PMLR 2021 [contents] - [i60]K. J. Joseph, Salman H. Khan, Fahad Shahbaz Khan, Vineeth N. Balasubramanian:
Towards Open World Object Detection. CoRR abs/2103.02603 (2021) - [i59]Piyushi Manupriya, Saketha Nath Jagarlapudi, Tarun Ram Menta, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. CoRR abs/2104.09073 (2021) - [i58]Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian:
Instance-wise Causal Feature Selection for Model Interpretation. CoRR abs/2104.12759 (2021) - [i57]Thrupthi Ann John, Vineeth N. Balasubramanian, C. V. Jawahar:
Canonical Saliency Maps: Decoding Deep Face Models. CoRR abs/2105.01386 (2021) - [i56]Gaurav Bhatt, Shivam Chandhok, Vineeth N. Balasubramanian:
Learn from Anywhere: Rethinking Generalized Zero-Shot Learning with Limited Supervision. CoRR abs/2107.04952 (2021) - [i55]Shivam Chandhok, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Vineeth N. Balasubramanian, Fahad Shahbaz Khan, Ling Shao:
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains. CoRR abs/2107.05622 (2021) - [i54]Puneet Mangla, Shivam Chandhok, Vineeth N. Balasubramanian, Fahad Shahbaz Khan:
Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains. CoRR abs/2107.07497 (2021) - [i53]Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar, Vineeth N. Balasubramanian:
Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach. CoRR abs/2108.11761 (2021) - [i52]Prachi Garg, Rohit Saluja, Vineeth N. Balasubramanian, Chetan Arora, Anbumani Subramanian, C. V. Jawahar:
Multi-Domain Incremental Learning for Semantic Segmentation. CoRR abs/2110.12205 (2021) - [i51]Anindya Sarkar, Anirban Sarkar, Sowrya Gali, Vineeth N. Balasubramanian:
Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach. CoRR abs/2111.00295 (2021) - [i50]Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi:
Feature Generation for Long-tail Classification. CoRR abs/2111.05956 (2021) - [i49]Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Amit Sharma:
Causal Regularization Using Domain Priors. CoRR abs/2111.12490 (2021) - [i48]Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian:
On Causally Disentangled Representations. CoRR abs/2112.05746 (2021) - 2020
- [j8]Kee-Eung Kim, Vineeth N. Balasubramanian:
Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020). Mach. Learn. 109(12): 2243-2245 (2020) - [j7]Vaibhav B. Sinha, Sneha Kudugunta, Adepu Ravi Sankar, Surya Teja Chavali, Vineeth N. Balasubramanian:
DANTE: Deep alternations for training neural networks. Neural Networks 131: 127-143 (2020) - [c71]Udit Maniyar, K. J. Joseph, Aniket Anand Deshmukh, Ürün Dogan, Vineeth N. Balasubramanian:
Zero-Shot Domain Generalization. BMVC 2020 - [c70]Shyam Nandan Rai, Vineeth N. Balasubramanian, Anbumani Subramanian, C. V. Jawahar:
Spatial Feedback Learning to Improve Semantic Segmentation in Hot Weather. BMVC 2020 - [c69]Saurabh Ravindranath, Rahul Baburaj, Vineeth N. Balasubramanian, NageswaraRao Namburu, Sujit Gujar, C. V. Jawahar:
Human-Machine Collaboration for Face Recognition. COMAD/CODS 2020: 10-18 - [c68]Sai Vikas Desai, Vineeth N. Balasubramanian:
Towards Fine-grained Sampling for Active Learning in Object Detection. CVPR Workshops 2020: 4010-4014 - [c67]Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Attributional Robustness Training Using Input-Gradient Spatial Alignment. ECCV (27) 2020: 515-533 - [c66]Sakshi Varshney, P. K. Srijith, Vineeth N. Balasubramanian:
STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse. ICONIP (5) 2020: 676-684