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05/22/2023
Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data
Real-world data tends to follow a long-tailed distribution, where the cl...
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12/06/2022
Open World DETR: Transformer based Open World Object Detection
Open world object detection aims at detecting objects that are absent in...
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05/09/2022
Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning
Incremental few-shot object detection aims at detecting novel classes wi...
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03/26/2022
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
A fundamental and challenging problem in deep learning is catastrophic f...
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02/01/2022
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation
Over the past years, semantic segmentation, as many other tasks in compu...
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11/19/2021
Global and Local Alignment Networks for Unpaired Image-to-Image Translation
The goal of unpaired image-to-image translation is to produce an output ...
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11/19/2021
Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
In autonomous driving, learning a segmentation model that can adapt to v...
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10/28/2021
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
Deep networks have shown remarkable results in the task of object detect...
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05/28/2021
Transformer-Based Source-Free Domain Adaptation
In this paper, we study the task of source-free domain adaptation (SFDA)...
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03/22/2021
Transformers Solve the Limited Receptive Field for Monocular Depth Prediction
While convolutional neural networks have shown a tremendous impact on va...
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03/05/2021
Variational Structured Attention Networks for Deep Visual Representation Learning
Convolutional neural networks have enabled major progress in addressing ...
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02/12/2020