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- Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation
- Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos
- Monocular Vision based Crowdsourced 3D Traffic Sign Positioning with Unknown Camera Intrinsics and Distortion Coefficients
- Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning Approach
- Knowledge Distillation Beyond Model Compression
- Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks
- Noisy Concurrent Training for Efficient Learning under Label Noise
- AI-Driven Road Maintenance Inspection v2:Reducing Data Dependency & Quantifying Road Damage
- Improving Generalization and Robustness with Noisy Collaboration in Knowledge Distillation
- RGPNet: A Real-Time General Purpose Semantic Segmentation
- Perceptual Loss for Robust Unsupervised Homography Estimation
- Distill on the Go: Online knowledge distillation in self-supervised learning
- Highlighting the Importance of Reducing Research Bias and Carbon Emissions in CNNs
- Improving the Efficiency of Transformers for Resource-Constrained Devices
- Self-Supervised Pretraining for Scene Change Detection
- Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices
- Does Thermal data make the detection systems more reliable?
- A Comprehensive Study of Vision Transformers on Dense Prediction Tasks
- Transformers In Self-Supervised Monocular Depth Estimation With Unknown Camera Intrinsics
- Learning Fast, Learning Slow: A General Contintual Learning Method Based On Complementary Learning System
- Synergy Between Synaptic Consolidation And Experience Replay For General Continual Learning
- Consistency Is The Key To Further Mitigating Catastrophic Forgetting In Continual Learning
- Task Agnostic Representation Consolidation: A Self Supervised Based Continual Learning Approach
- Inbiased: Inductive Bias Distillation To Improve Generalization And Robustness Through Shape-Awareness
- Curbing Task Interference Using Representation Similarity-Guided Multi-Task Feature Sharing
- Differencing Based Self-Supervised Pretraining For Scene Change Detection
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