Avinash Ravichandran

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 54

Top Topics

Incremental Learning

Diffusion Models

Top Venues

Publications

Nirat Saini, Navaneeth Bodla, Ashish Shrivastava, Avinash Ravichandran, Xiao Zhang, Abhinav Shrivastava, Bharat Singh
InVi: Object Insertion In Videos Using Off-the-Shelf Diffusion Models. CoRR (2024)
Bharat Singh, Viveka Kulharia, Luyu Yang, Avinash Ravichandran, Ambrish Tyagi, Ashish Shrivastava
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR. CoRR (2024)
Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto
A Meta-Learning Approach to Predicting Performance and Data Requirements. CVPR (2023)
Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto
Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models. CoRR (2023)
Jongheon Jeong, Yang Zou, Taewan Kim, Dongqing Zhang, Avinash Ravichandran, Onkar Dabeer
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation. CoRR (2023)
Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless C. Fowlkes, Ashwin Swaminathan, Stefano Soatto
Your representations are in the network: composable and parallel adaptation for large scale models. NeurIPS (2023)
Gukyeong Kwon, Zhaowei Cai, Avinash Ravichandran, Erhan Bas, Rahul Bhotika, Stefano Soatto
Masked Vision and Language Modeling for Multi-modal Representation Learning. ICLR (2023)
Rajshekhar Das, Yonatan Dukler, Avinash Ravichandran, Ashwin Swaminathan
Learning Expressive Prompting With Residuals for Vision Transformers. CoRR (2023)
Rajshekhar Das, Yonatan Dukler, Avinash Ravichandran, Ashwin Swaminathan
Learning Expressive Prompting With Residuals for Vision Transformers. CVPR (2023)
Jongheon Jeong, Yang Zou, Taewan Kim, Dongqing Zhang, Avinash Ravichandran, Onkar Dabeer
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation. CVPR (2023)
Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto
A Meta-Learning Approach to Predicting Performance and Data Requirements. CoRR (2023)
Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, Stefano Soatto
Semi-supervised Vision Transformers at Scale. NeurIPS (2022)
Achin Jain, Kibok Lee, Gurumurthy Swaminathan, Hao Yang, Bernt Schiele, Avinash Ravichandran, Onkar Dabeer
ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers. CoRR (2022)
Zhaowei Cai, Gukyeong Kwon, Avinash Ravichandran, Erhan Bas, Zhuowen Tu, Rahul Bhotika, Stefano Soatto
X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks. ECCV (36) (2022)
Zhaowei Cai, Gukyeong Kwon, Avinash Ravichandran, Erhan Bas, Zhuowen Tu, Rahul Bhotika, Stefano Soatto
X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks. CoRR (2022)
Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto
Task Adaptive Parameter Sharing for Multi-Task Learning. CoRR (2022)
Tz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li, Avinash Ravichandran, Nuno Vasconcelos, Rahul Bhotika, Stefano Soatto
Class-Incremental Learning with Strong Pre-trained Models. CVPR (2022)
Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto
Task Adaptive Parameter Sharing for Multi-Task Learning. CVPR (2022)
Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto
DIVA: Dataset Derivative of a Learning Task. ICLR (2022)
Gukyeong Kwon, Zhaowei Cai, Avinash Ravichandran, Erhan Bas, Rahul Bhotika, Stefano Soatto
Masked Vision and Language Modeling for Multi-modal Representation Learning. CoRR (2022)
Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, Stefano Soatto
Semi-supervised Vision Transformers at Scale. CoRR (2022)
Tz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li, Avinash Ravichandran, Nuno Vasconcelos, Rahul Bhotika, Stefano Soatto
Class-Incremental Learning with Strong Pre-trained Models. CoRR (2022)
Kibok Lee, Hao Yang, Satyaki Chakraborty, Zhaowei Cai, Gurumurthy Swaminathan, Avinash Ravichandran, Onkar Dabeer
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark. CoRR (2022)
Kibok Lee, Hao Yang, Satyaki Chakraborty, Zhaowei Cai, Gurumurthy Swaminathan, Avinash Ravichandran, Onkar Dabeer
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark. ECCV (20) (2022)
Zhaowei Cai, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Zhuowen Tu, Stefano Soatto
Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning. CoRR (2021)
Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto
Uniform Sampling over Episode Difficulty. CoRR (2021)
Aditya Deshpande, Alessandro Achille, Avinash Ravichandran, Hao Li, Luca Zancato, Charless C. Fowlkes, Rahul Bhotika, Stefano Soatto, Pietro Perona
A linearized framework and a new benchmark for model selection for fine-tuning. CoRR (2021)
Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto
Uniform Sampling over Episode Difficulty. NeurIPS (2021)
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Estimating informativeness of samples with Smooth Unique Information. ICLR (2021)
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Estimating informativeness of samples with Smooth Unique Information. CoRR (2021)
Orchid Majumder, Avinash Ravichandran, Subhransu Maji, Marzia Polito, Rahul Bhotika, Stefano Soatto
Revisiting Contrastive Learning for Few-Shot Classification. CoRR (2021)
Aditya Golatkar, Alessandro Achille, Avinash Ravichandran, Marzia Polito, Stefano Soatto
Mixed-Privacy Forgetting in Deep Networks. CVPR (2021)
Alessandro Achille, Aditya Golatkar, Avinash Ravichandran, Marzia Polito, Stefano Soatto
LQF: Linear Quadratic Fine-Tuning. CVPR (2021)
Zhizhong Li, Avinash Ravichandran, Charless C. Fowlkes, Marzia Polito, Rahul Bhotika, Stefano Soatto
Representation Consolidation for Training Expert Students. CoRR (2021)
Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto
DIVA: Dataset Derivative of a Learning Task. CoRR (2021)
Zhaowei Cai, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Zhuowen Tu, Stefano Soatto
Exponential Moving Average Normalization for Self-Supervised and Semi-Supervised Learning. CVPR (2021)
Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Continual Universal Object Detection. CoRR (2020)
Aditya Golatkar, Alessandro Achille, Avinash Ravichandran, Marzia Polito, Stefano Soatto
Mixed-Privacy Forgetting in Deep Networks. CoRR (2020)
Qing Liu, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Incremental Learning for Metric-Based Meta-Learners. CoRR (2020)
Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Rethinking the Hyperparameters for Fine-tuning. CoRR (2020)
Luca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Predicting Training Time Without Training. CoRR (2020)
Guneet Singh Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto
A Baseline for Few-Shot Image Classification. ICLR (2020)
Luca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Predicting Training Time Without Training. NeurIPS (2020)
Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Rethinking the Hyperparameters for Fine-tuning. ICLR (2020)
Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Incremental Few-Shot Meta-learning via Indirect Discriminant Alignment. ECCV (7) (2020)
Alessandro Achille, Aditya Golatkar, Avinash Ravichandran, Marzia Polito, Stefano Soatto
LQF: Linear Quadratic Fine-Tuning. CoRR (2020)
Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training. CoRR (2019)
Alessandro Achille, Michael Lam, Rahul Tewari, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Stefano Soatto, Pietro Perona
Task2Vec: Task Embedding for Meta-Learning. CoRR (2019)
István Fehérvári, Avinash Ravichandran, Srikar Appalaraju
Unbiased Evaluation of Deep Metric Learning Algorithms. CoRR (2019)
Kwonjoon Lee, Subhransu Maji, Avinash Ravichandran, Stefano Soatto
Meta-Learning with Differentiable Convex Optimization. CoRR (2019)
Guneet S. Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto
A Baseline for Few-Shot Image Classification. CoRR (2019)
Kwonjoon Lee, Subhransu Maji, Avinash Ravichandran, Stefano Soatto
Meta-Learning With Differentiable Convex Optimization. CVPR (2019)
Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training. ICCV (2019)
Alessandro Achille, Michael Lam, Rahul Tewari, Avinash Ravichandran, Subhransu Maji, Charless C. Fowlkes, Stefano Soatto, Pietro Perona
Task2Vec: Task Embedding for Meta-Learning. ICCV (2019)
Vasiliy Karasev, Avinash Ravichandran, Stefano Soatto
Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation. CVPR (2014)
Avinash Ravichandran, Rizwan Chaudhry, René Vidal
Categorizing Dynamic Textures Using a Bag of Dynamical Systems. IEEE Trans. Pattern Anal. Mach. Intell. 35 (2) (2013)
Brian Taylor, Alper Ayvaci, Avinash Ravichandran, Stefano Soatto
Semantic Video Segmentation from Occlusion Relations within a Convex Optimization Framework. EMMCVPR (2013)
Daniele Perrone, Avinash Ravichandran, René Vidal, Paolo Favaro
Image Priors for Image Deblurring with Uncertain Blur. BMVC (2012)
Avinash Ravichandran, Stefano Soatto
Long-Range Spatio-Temporal Modeling of Video with Application to Fire Detection. ECCV (2) (2012)
Avinash Ravichandran, Chaohui Wang, Michalis Raptis, Stefano Soatto
SuperFloxels: A Mid-level Representation for Video Sequences. ECCV Workshops (3) (2012)
Bijan Afsari, Rizwan Chaudhry, Avinash Ravichandran, René Vidal
Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynamic scenes. CVPR (2012)
Avinash Ravichandran, René Vidal
Video Registration Using Dynamic Textures. IEEE Trans. Pattern Anal. Mach. Intell. 33 (1) (2011)
Paolo Favaro, René Vidal, Avinash Ravichandran
A closed form solution to robust subspace estimation and clustering. CVPR (2011)
Avinash Ravichandran, Paolo Favaro, René Vidal
A Unified Approach to Segmentation and Categorization of Dynamic Textures. ACCV (1) (2010)
Avinash Ravichandran, Rizwan Chaudhry, René Vidal
View-invariant dynamic texture recognition using a bag of dynamical systems. CVPR (2009)
Rizwan Chaudhry, Avinash Ravichandran, Gregory D. Hager, René Vidal
Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions. CVPR (2009)
Avinash Ravichandran, René Vidal
Video Registration Using Dynamic Textures. ECCV (2) (2008)
Avinash Ravichandran, René Vidal, Henry R. Halperin
Segmenting a beating heart using polysegment and Spatial GPCA. ISBI (2006)
René Vidal, Avinash Ravichandran
Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures. CVPR (2) (2005)