574 citations · 643 across the 6 of their papers we have counts for
11 papers · 1 filter
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Dequan Wang, Xiaosong Wang, Lilong Wang +12
Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enabl…
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud
Mong H. Ng, Kaahan Radia, Jianfei Chen +3
Bird's-eye-view (BEV) is a powerful and widely adopted representation for road scenes that captures surrounding objects and their spatial locations, along with overall context in t…
CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs
Zhen Dong, Dequan Wang, Qijing Huang +6
Deploying deep learning models on embedded systems has been challenging due to limited computing resources. The majority of existing work focuses on accelerating image classificati…
Dynamic Scale Inference by Entropy Minimization
Dequan Wang, Evan Shelhamer, Bruno Olshausen +1
Given the variety of the visual world there is not one true scale for recognition: objects may appear at drastically different sizes across the visual field. Rather than enumerate…
Monocular Plan View Networks for Autonomous Driving
Dequan Wang, Coline Devin, Qi-Zhi Cai +2
Convolutions on monocular dash cam videos capture spatial invariances in the image plane but do not explicitly reason about distances and depth. We propose a simple transformation…
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields
Evan Shelhamer, Dequan Wang, Trevor Darrell
The visual world is vast and varied, but its variations divide into structured and unstructured factors. We compose free-form filters and structured Gaussian filters, optimized end…