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04/21/2023
Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation
Using multiple spatial modalities has been proven helpful in improving s...
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03/19/2023
Trainable Projected Gradient Method for Robust Fine-tuning
Recent studies on transfer learning have shown that selectively fine-tun...
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10/07/2022
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks
Adapting large-scale pretrained models to various downstream tasks via f...
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08/29/2022
Open-Set Semi-Supervised Object Detection
Recent developments for Semi-Supervised Object Detection (SSOD) have sho...
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06/19/2022
Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors
With the recent development of Semi-Supervised Object Detection (SS-OD) ...
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11/25/2021
Cross-Domain Object Detection via Adaptive Self-Training
We tackle the problem of domain adaptation in object detection, where th...
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07/01/2021
Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking
In this paper, we address bandwidth-limited and obstruction-prone collab...
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07/01/2021
Enhancing Multi-Robot Perception via Learned Data Association
In this paper, we address the multi-robot collaborative perception probl...
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02/18/2021
Unbiased Teacher for Semi-Supervised Object Detection
Semi-supervised learning, i.e., training networks with both labeled and ...
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10/22/2020
Posterior Re-calibration for Imbalanced Datasets
Neural Networks can perform poorly when the training label distribution ...
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05/30/2020
When2com: Multi-Agent Perception via Communication Graph Grouping
While significant advances have been made for single-agent perception, m...
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03/21/2020
Who2com: Collaborative Perception via Learnable Handshake Communication
In this paper, we propose the problem of collaborative perception, where...
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11/06/2019
UNO: Uncertainty-aware Noisy-Or Multimodal Fusion for Unanticipated Input Degradation
The fusion of multiple sensor modalities, especially through deep learni...
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04/08/2019
A Closer Look at Few-shot Classification
Few-shot classification aims to learn a classifier to recognize unseen c...
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10/30/2018
Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines
Continual learning has received a great deal of attention recently with ...
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04/25/2018
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
Person re-identification (Re-ID) aims at recognizing the same person fro...
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05/03/2017
