111 citations · 734 across the 50 of their papers we have counts for
10 papers · 1 filter
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen +1
This paper proposes two novel techniques to train deep convolutional neural networks with low bit-width weights and activations. First, to obtain low bit-width weights, most existi…
Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large Scenes
Qi Zhang, Antoni B. Chan
Crowd counting in single-view images has achieved outstanding performance on existing counting datasets. However, single-view counting is not applicable to large and wide scenes (e…
ALdataset: a benchmark for pool-based active learning
Xueying Zhan, Antoni Bert Chan
Active learning (AL) is a subfield of machine learning (ML) in which a learning algorithm could achieve good accuracy with less training samples by interactively querying a user/or…
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
Ziquan Liu, Yufei Cui, Antoni B. Chan
Using weight decay to penalize the L2 norms of weights in neural networks has been a standard training practice to regularize the complexity of networks. In this paper, we show tha…
Tracking-by-Counting: Using Network Flows on Crowd Density Maps for Tracking Multiple Targets
Weihong Ren, Xinchao Wang, Jiandong Tian +2
State-of-the-art multi-object tracking~(MOT) methods follow the tracking-by-detection paradigm, where object trajectories are obtained by associating per-frame outputs of object de…
Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets
Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1
A wide range of image captioning models has been developed, achieving significant improvement based on popular metrics, such as BLEU, CIDEr, and SPICE. However, although the genera…
Fine-Grained Crowd Counting
Jia Wan, Nikil Senthil Kumar, Antoni B. Chan
Current crowd counting algorithms are only concerned about the number of people in an image, which lacks low-level fine-grained information of the crowd. For many practical applica…
Single-Frame based Deep View Synchronization for Unsynchronized Multi-Camera Surveillance
Qi Zhang, Antoni B. Chan
Multi-camera surveillance has been an active research topic for understanding and modeling scenes. Compared to a single camera, multi-cameras provide larger field-of-view and more…
Over-crowdedness Alert! Forecasting the Future Crowd Distribution
Yuzhen Niu, Weifeng Shi, Wenxi Liu +3
In recent years, vision-based crowd analysis has been studied extensively due to its practical applications in real world. In this paper, we formulate a novel crowd analysis proble…
3D Crowd Counting via Geometric Attention-guided Multi-View Fusion
Qi Zhang, Antoni B. Chan
Recently multi-view crowd counting using deep neural networks has been proposed to enable counting in large and wide scenes using multiple cameras. The current methods project the…