Cvpr2020 Oral Multi Dimensional Pruning

Media Summary: Authors: Patra, Rishabh; Hebbalaguppe, Ramya*; Dash, Tirtharaj; Shroff, Gautam; Vig, Lovekesh Description: Deep neural ... We address the generalization ability of recent learning-based point cloud registration methods. Despite their success, these ... Official presentation on Park et al., "Training Debiased Subnetworks with Contrastive Weight

Cvpr2020 Oral Multi Dimensional Pruning - Detailed Analysis & Overview

Authors: Patra, Rishabh; Hebbalaguppe, Ramya*; Dash, Tirtharaj; Shroff, Gautam; Vig, Lovekesh Description: Deep neural ... We address the generalization ability of recent learning-based point cloud registration methods. Despite their success, these ... Official presentation on Park et al., "Training Debiased Subnetworks with Contrastive Weight This work defines and solves the scene de-occlusion problem without manual annotations of ordering or amodal masks. Closing Remarks of the "Continual Learning in Computer Vision" Workshop at In this episode, Ben Sorscher, a PhD student at Stanford, sheds light on the challenges posed by the ever-increasing size of data ...

5-minute talk for the following paper: Min-Hung Chen, Baopu Li, Yingze Bao, Ghassan AlRegib, and Zsolt Kira, “Action ... Video presentation accompanying the paper published at IEEE Big Data 2021, Orlando, USA. Paper: ...

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[CVPR2020 Oral] Multi-Dimensional Pruning: A Unified Framework for Model Compression

MDP: Multidimensional Vision Model Pruning with Latency Constraint - CVPR 2025

Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning

[CVPR 2021, oral] PointNetLK Revisited

[CVPR 2020 Oral] Quick intro to High-dimensional ConvNets for Geometric Pattern Recognition

Training Debiased Subnetworks with Contrastive Weight Pruning (CVPR 2023)

CVPR 2020 oral paper "Self-Supervised Scene De-occlusion" (click CC for subtitles)

[CLVision @ CVPR2020] Closing Remarks

Data Pruning for Efficient Machine Learning | Ben Sorscher | Eye on AI #117

SSTDA (CVPR 2020) 5-min Talk

EfficientML.ai Lecture 3 - Pruning and Sparsity (Part I) (MIT 6.5940, Fall 2023)

CUP: Cluster Pruning for Compressing Deep Neural Networks

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[CVPR2020 Oral] Multi-Dimensional Pruning: A Unified Framework for Model Compression

[CVPR2020 Oral] Multi-Dimensional Pruning: A Unified Framework for Model Compression

Paper on: ...

MDP: Multidimensional Vision Model Pruning with Latency Constraint - CVPR 2025

MDP: Multidimensional Vision Model Pruning with Latency Constraint - CVPR 2025

MDP:

Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning

Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning

Authors: Patra, Rishabh; Hebbalaguppe, Ramya*; Dash, Tirtharaj; Shroff, Gautam; Vig, Lovekesh Description: Deep neural ...

[CVPR 2021, oral] PointNetLK Revisited

[CVPR 2021, oral] PointNetLK Revisited

We address the generalization ability of recent learning-based point cloud registration methods. Despite their success, these ...

[CVPR 2020 Oral] Quick intro to High-dimensional ConvNets for Geometric Pattern Recognition

[CVPR 2020 Oral] Quick intro to High-dimensional ConvNets for Geometric Pattern Recognition

We present high

Training Debiased Subnetworks with Contrastive Weight Pruning (CVPR 2023)

Training Debiased Subnetworks with Contrastive Weight Pruning (CVPR 2023)

Official presentation on Park et al., "Training Debiased Subnetworks with Contrastive Weight

CVPR 2020 oral paper "Self-Supervised Scene De-occlusion" (click CC for subtitles)

CVPR 2020 oral paper "Self-Supervised Scene De-occlusion" (click CC for subtitles)

This work defines and solves the scene de-occlusion problem without manual annotations of ordering or amodal masks.

[CLVision @ CVPR2020] Closing Remarks

[CLVision @ CVPR2020] Closing Remarks

Closing Remarks of the "Continual Learning in Computer Vision" Workshop at

Data Pruning for Efficient Machine Learning | Ben Sorscher | Eye on AI #117

Data Pruning for Efficient Machine Learning | Ben Sorscher | Eye on AI #117

In this episode, Ben Sorscher, a PhD student at Stanford, sheds light on the challenges posed by the ever-increasing size of data ...

SSTDA (CVPR 2020) 5-min Talk

SSTDA (CVPR 2020) 5-min Talk

5-minute talk for the following paper: Min-Hung Chen, Baopu Li, Yingze Bao, Ghassan AlRegib, and Zsolt Kira, “Action ...

EfficientML.ai Lecture 3 - Pruning and Sparsity (Part I) (MIT 6.5940, Fall 2023)

EfficientML.ai Lecture 3 - Pruning and Sparsity (Part I) (MIT 6.5940, Fall 2023)

EfficientML.ai Lecture 3 -

CUP: Cluster Pruning for Compressing Deep Neural Networks

CUP: Cluster Pruning for Compressing Deep Neural Networks

Video presentation accompanying the paper published at IEEE Big Data 2021, Orlando, USA. Paper: ...

MUXConv: Information Multiplexing in Convolutional Neural Networks (CVPR 2020)

MUXConv: Information Multiplexing in Convolutional Neural Networks (CVPR 2020)

CVPR 2020