Search Results for author:
Found 10 papers, 4 papers with code
Far3D: Expanding the Horizon for Surround-view 3D Object Detection
Recently 3D object detection from surround-view images has made notable advancements with its low deployment cost.
Ranked #1 on
3D Object Detection
on nuScenes Camera Only
OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation
This paper presents OmniDataComposer, an innovative approach for multimodal data fusion and unlimited data generation with an intent to refine and uncomplicate interplay among diverse data modalities.
Ranked #10 on
Zero-Shot Video Question Answer
on MSRVTT-QA
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
On the standard nuScenes benchmark, it is the first online multi-view method that achieves comparable performance (67. 6% NDS & 65. 3% AMOTA) with lidar-based methods.
Ranked #1 on
3D Multi-Object Tracking
on nuScenes Camera Only
Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection
The 3D-to-2D perspective inconsistency and global attention lead to a weak correlation between foreground tokens and queries, resulting in slow convergence.
Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans
The experimental results show that our automatically searched models (CovidNet3D) outperform the baseline human-designed models on the three datasets with tens of times smaller model size and higher accuracy.
Logic-based switching finite-time stabilization with applications in mechanical systems
Different from the existing adaptive controllers for structured/parametric uncertainties, a new switching barrier Lyapunov method and supervisory functions are introduced to overcome the obstacles caused by unstructured uncertainties and unknown control directions.
PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning
Weight pruning of DNNs is proposed, but existing schemes represent two extremes in the design space: non-structured pruning is fine-grained, accurate, but not hardware friendly; structured pruning is coarse-grained, hardware-efficient, but with higher accuracy loss.
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models
Our results show that object detection can help improve the accuracy of some skin disease classes.
CNN-MERP: An FPGA-Based Memory-Efficient Reconfigurable Processor for Forward and Backward Propagation of Convolutional Neural Networks
Under limited DRAM bandwidth, a system throughput of 1244GFlop/s is achieved at the Vertex UltraScale platform, which is 5. 48 times higher than the state-of-the-art FPGA implementations.
Chain-NN: An Energy-Efficient 1D Chain Architecture for Accelerating Deep Convolutional Neural Networks
This achieves a peak throughput of 806. 4GOPS with 567. 5mW and is able to accelerate the five convolutional layers in AlexNet at a frame rate of 326. 2fps.
