activity
20112023
most citedCrowd Counting and Density Estimation by Trellis Encoder-Decoder Network

78 citations · 378 across the 37 of their papers we have counts for

collaborators

37 papers

cs.CV2023★ 1 cited

Representation Disparity-aware Distillation for 3D Object Detection

Yanjing Li, Sheng Xu, Mingbao Lin +3

In this paper, we focus on developing knowledge distillation (KD) for compact 3D detectors. We observe that off-the-shelf KD methods manifest their efficacy only when the teacher m…

cs.CV2023★ 3 cited

Q-YOLO: Efficient Inference for Real-time Object Detection

Mingze Wang, Huixin Sun, Jun Shi +3

Real-time object detection plays a vital role in various computer vision applications. However, deploying real-time object detectors on resource-constrained platforms poses challen…

cs.CV2023★ 1 cited

DCP-NAS: Discrepant Child-Parent Neural Architecture Search for 1-bit CNNs

Yanjing Li, Sheng Xu, Xianbin Cao +4

Neural architecture search (NAS) proves to be among the effective approaches for many tasks by generating an application-adaptive neural architecture, which is still challenged by…

cs.CV2023★ 3 cited

Bi-ViT: Pushing the Limit of Vision Transformer Quantization

Yanjing Li, Sheng Xu, Mingbao Lin +4

Vision transformers (ViTs) quantization offers a promising prospect to facilitate deploying large pre-trained networks on resource-limited devices. Fully-binarized ViTs (Bi-ViT) th…

cs.CV2023★ 1 cited

Uncertainty-Aware Gradient Stabilization for Small Object Detection

Huixin Sun, Yanjing Li, Linlin Yang +2

Despite advances in generic object detection, there remains a performance gap in detecting small objects compared to normal-scale objects. We reveal that conventional object locali…

cs.CV2022★ 31 cited

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

Yanjing Li, Sheng Xu, Baochang Zhang +3

The large pre-trained vision transformers (ViTs) have demonstrated remarkable performance on various visual tasks, but suffer from expensive computational and memory cost problems…