Media Summary: This video accompanies our publication: Aditya Singh and Haohan Wang, Presentation for the paper: Amin Parchami-Araghi*, Moritz Böhle*, Sukrut Rao*, Bernt Schiele. Good Teachers Explain: ... [ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration

Eccv 2024 Simple Unsupervised Knowledge - Detailed Analysis & Overview

This video accompanies our publication: Aditya Singh and Haohan Wang, Presentation for the paper: Amin Parchami-Araghi*, Moritz Böhle*, Sukrut Rao*, Bernt Schiele. Good Teachers Explain: ... [ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration Title: Efficient Bias Mitigation Without Privileged Information Authors: Mateo Espinosa Zarlenga, Swami Sankaranarayanan, ... Title: Adaptive Correspondence Scoring for This paper addresses the critical issue of miscalibration in CLIP-based model adaptation, particularly in the challenging scenario ...

We empirically demonstrate that popular CLIP adaptation approaches, such as Adapters, Prompt Learning, and Test-Time ... Authors: Ponimatkin, Georgy*; Samet, Nermin; Xiao, Yang; Du, Yuming; Marlet, Renaud; Lepetit, Vincent Description: We propose ...

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ECCV 2024 - Simple Unsupervised Knowledge Distillation With Space Similarity
[ECCV 2024] Good Teachers Explain: Explanation-enhanced Knowledge Distillation
[ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration
[ECCV 2024 Oral][Indepth Reading]Efficient Bias Mitigation Without Privileged Information
ECCV 2024 Paper: Unsqueeze [cls] Bottleneck to Learn Rich Representations
[ECCV 2024 Oral][Indepth Reading]Adaptive Correspondence Scoring for Unsupervised Medical Image Regi
[ECCV 2024] Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection
ECCV 2024 Video Summary - Improving Medical Multi-modal Contrastive Learning with Expert Annotations
[ECCV 2024] FinePseudo: Semi-Supervised Fine-Grained Action Recognition
ECCV 2024: Robust Calibration of Large Vision-Language Adapters
[ECCV 2024 Oral] Decoupling Common & Unique Representations for Multimodal Self-supervised Learning
ECCV 2024 Redux: Day 1 - Robust Calibration of Large Vision-Language Adapters
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ECCV 2024 - Simple Unsupervised Knowledge Distillation With Space Similarity

ECCV 2024 - Simple Unsupervised Knowledge Distillation With Space Similarity

This video accompanies our publication: Aditya Singh and Haohan Wang,

[ECCV 2024] Good Teachers Explain: Explanation-enhanced Knowledge Distillation

[ECCV 2024] Good Teachers Explain: Explanation-enhanced Knowledge Distillation

Presentation for the paper: Amin Parchami-Araghi*, Moritz Böhle*, Sukrut Rao*, Bernt Schiele. Good Teachers Explain: ...

[ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration

[ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration

[ECCV 2024 Oral] Adaptive Correspondence Scoring for Unsupervised Medical Image Registration

[ECCV 2024 Oral][Indepth Reading]Efficient Bias Mitigation Without Privileged Information

[ECCV 2024 Oral][Indepth Reading]Efficient Bias Mitigation Without Privileged Information

Title: Efficient Bias Mitigation Without Privileged Information Authors: Mateo Espinosa Zarlenga, Swami Sankaranarayanan, ...

ECCV 2024 Paper: Unsqueeze [cls] Bottleneck to Learn Rich Representations

ECCV 2024 Paper: Unsqueeze [cls] Bottleneck to Learn Rich Representations

ECCV 2024

[ECCV 2024 Oral][Indepth Reading]Adaptive Correspondence Scoring for Unsupervised Medical Image Regi

[ECCV 2024 Oral][Indepth Reading]Adaptive Correspondence Scoring for Unsupervised Medical Image Regi

Title: Adaptive Correspondence Scoring for

[ECCV 2024] Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection

[ECCV 2024] Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection

Video Explanation for the paper, [

ECCV 2024 Video Summary - Improving Medical Multi-modal Contrastive Learning with Expert Annotations

ECCV 2024 Video Summary - Improving Medical Multi-modal Contrastive Learning with Expert Annotations

The video summarizes our

[ECCV 2024] FinePseudo: Semi-Supervised Fine-Grained Action Recognition

[ECCV 2024] FinePseudo: Semi-Supervised Fine-Grained Action Recognition

https://daveishan.github.io/finepsuedo-webpage/

ECCV 2024: Robust Calibration of Large Vision-Language Adapters

ECCV 2024: Robust Calibration of Large Vision-Language Adapters

This paper addresses the critical issue of miscalibration in CLIP-based model adaptation, particularly in the challenging scenario ...

[ECCV 2024 Oral] Decoupling Common & Unique Representations for Multimodal Self-supervised Learning

[ECCV 2024 Oral] Decoupling Common & Unique Representations for Multimodal Self-supervised Learning

Paper: https://arxiv.org/abs/2309.05300 Code: https://github.com/zhu-xlab/DeCUR.

ECCV 2024 Redux: Day 1 - Robust Calibration of Large Vision-Language Adapters

ECCV 2024 Redux: Day 1 - Robust Calibration of Large Vision-Language Adapters

We empirically demonstrate that popular CLIP adaptation approaches, such as Adapters, Prompt Learning, and Test-Time ...

A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation

A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation

Authors: Ponimatkin, Georgy*; Samet, Nermin; Xiao, Yang; Du, Yuming; Marlet, Renaud; Lepetit, Vincent Description: We propose ...