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Found 11 papers, 7 papers with code
CVPR 2023 Text Guided Video Editing Competition
In this paper we present a retrospective on the competition and describe the winning method.
Dataset Condensation for Recommendation
However, applying existing approaches to condense recommendation datasets is impractical due to following challenges: (i) sampling-based methods are inadequate in addressing the long-tailed distribution problem; (ii) synthesizing-based methods are not applicable due to discreteness of interactions and large size of recommendation datasets; (iii) neither of them fail to address the specific issue in recommendation of false negative items, where items with potential user interest are incorrectly sampled as negatives owing to insufficient exposure.
MAE-GEBD:Winning the CVPR'2023 LOVEU-GEBD Challenge
The Generic Event Boundary Detection (GEBD) task aims to build a model for segmenting videos into segments by detecting general event boundaries applicable to various classes.
Perturbation-Based Two-Stage Multi-Domain Active Learning
Active Learning (AL) presents an encouraging solution to this issue by annotating a smaller number of highly informative instances, thereby reducing the labeling effort.
Large Language Models can be Guided to Evade AI-Generated Text Detection
Large language models (LLMs) have shown remarkable performance in various tasks and have been extensively utilized by the public.
Multi-Domain Learning From Insufficient Annotations
Multi-domain learning (MDL) refers to simultaneously constructing a model or a set of models on datasets collected from different domains.
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier
Recent advances in neural collapse have shown that the classifiers and feature prototypes under perfect training scenarios collapse into an optimal structure called simplex equiangular tight frame (ETF).
D$^{\bf{3}}$: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos
In this paper, the duplicate detection is newly and precisely defined as occlusion misreporting on the same athlete by multiple detection boxes in one frame.
Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge
In this paper, we apply Masked Autoencoders to improve algorithm performance on the GEBD tasks.
Multi-Domain Active Learning: Literature Review and Comparative Study
Active learning (AL) can be utilized in MDL to reduce the labeling effort by only using the most informative data.
Adaptive Rank Estimate in Robust Principal Component Analysis
In this paper, an adaptive rank estimate based RPCA (ARE-RPCA) is proposed, which adaptively assigns weights on different singular values via rank estimation.
