3 citations · 16 across the 11 of their papers we have counts for
11 papers · 1 filter
Self-Supervised Multi-Object Tracking with Path Consistency
Zijia Lu, Bing Shuai, Yanbei Chen +2
In this paper, we propose a novel concept of path consistency to learn robust object matching without using manual object identity supervision. Our key idea is that, to track a obj…
Hyperbolic Learning with Synthetic Captions for Open-World Detection
Fanjie Kong, Yanbei Chen, Jiarui Cai +1
Open-world detection poses significant challenges, as it requires the detection of any object using either object class labels or free-form texts. Existing related works often use…
Denoising and Selecting Pseudo-Heatmaps for Semi-Supervised Human Pose Estimation
Zhuoran Yu, Manchen Wang, Yanbei Chen +2
We propose a new semi-supervised learning design for human pose estimation that revisits the popular dual-student framework and enhances it two ways. First, we introduce a denoisin…
Distilling Knowledge from Self-Supervised Teacher by Embedding Graph Alignment
Yuchen Ma, Yanbei Chen, Zeynep Akata
Recent advances have indicated the strengths of self-supervised pre-training for improving representation learning on downstream tasks. Existing works often utilize self-supervised…
Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval
Abhra Chaudhuri, Massimiliano Mancini, Yanbei Chen +2
Representation learning for sketch-based image retrieval has mostly been tackled by learning embeddings that discard modality-specific information. As instances from different moda…
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
Uddeshya Upadhyay, Shyamgopal Karthik, Yanbei Chen +2
High-quality calibrated uncertainty estimates are crucial for numerous real-world applications, especially for deep learning-based deployed ML systems. While Bayesian deep learning…
Attention Consistency on Visual Corruptions for Single-Source Domain Generalization
Ilke Cugu, Massimiliano Mancini, Yanbei Chen +1
Generalizing visual recognition models trained on a single distribution to unseen input distributions (i.e. domains) requires making them robust to superfluous correlations in the…
Probabilistic Compositional Embeddings for Multimodal Image Retrieval
Andrei Neculai, Yanbei Chen, Zeynep Akata
Existing works in image retrieval often consider retrieving images with one or two query inputs, which do not generalize to multiple queries. In this work, we investigate a more ch…
Robustness via Uncertainty-aware Cycle Consistency
Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata
Unpaired image-to-image translation refers to learning inter-image-domain mapping without corresponding image pairs. Existing methods learn deterministic mappings without explicitl…
Uncertainty-Guided Progressive GANs for Medical Image Translation
Uddeshya Upadhyay, Yanbei Chen, Tobias Hepp +2
Image-to-image translation plays a vital role in tackling various medical imaging tasks such as attenuation correction, motion correction, undersampled reconstruction, and denoisin…
Where and When: Space-Time Attention for Audio-Visual Explanations
Yanbei Chen, Thomas Hummel, A. Sophia Koepke +1
Explaining the decision of a multi-modal decision-maker requires to determine the evidence from both modalities. Recent advances in XAI provide explanations for models trained on s…