227 citations · 341 across the 26 of their papers we have counts for
8 papers · 1 filter
Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
Beier Zhu, Kaihua Tang, Qianru Sun +1
Foundation models like CLIP allow zero-shot transfer on various tasks without additional training data. Yet, the zero-shot performance is less competitive than a fully supervised o…
Invariant Training 2D-3D Joint Hard Samples for Few-Shot Point Cloud Recognition
Xuanyu Yi, Jiajun Deng, Qianru Sun +3
We tackle the data scarcity challenge in few-shot point cloud recognition of 3D objects by using a joint prediction from a conventional 3D model and a well-trained 2D model. Surpri…
Class-Incremental Exemplar Compression for Class-Incremental Learning
Zilin Luo, Yaoyao Liu, Bernt Schiele +1
Exemplar-based class-incremental learning (CIL) finetunes the model with all samples of new classes but few-shot exemplars of old classes in each incremental phase, where the "few-…
Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection
Hui Lv, Zhongqi Yue, Qianru Sun +3
Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the binary anomaly label is only given on the video level, but the output requires snippet-level prediction…
Semantic Scene Completion with Cleaner Self
Fengyun Wang, Dong Zhang, Hanwang Zhang +2
Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-p…
Compositional Prompt Tuning with Motion Cues for Open-vocabulary Video Relation Detection
Kaifeng Gao, Long Chen, Hanwang Zhang +2
Prompt tuning with large-scale pretrained vision-language models empowers open-vocabulary predictions trained on limited base categories, e.g., object classification and detection.…
RMM: Reinforced Memory Management for Class-Incremental Learning
Yaoyao Liu, Bernt Schiele, Qianru Sun
Class-Incremental Learning (CIL) [40] trains classifiers under a strict memory budget: in each incremental phase, learning is done for new data, most of which is abandoned to free…
Online Hyperparameter Optimization for Class-Incremental Learning
Yaoyao Liu, Yingying Li, Bernt Schiele +1
Class-incremental learning (CIL) aims to train a classification model while the number of classes increases phase-by-phase. An inherent challenge of CIL is the stability-plasticity…