961 citations · 1.1k across the 9 of their papers we have counts for
10 papers
HaloBlock: Faster and Better Decoding for Diffusion Large Language Models
Zhaohui Zheng, Chenhang He, Jinrui Zhang +2
Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding. However, there are two issue…
DEL: Digit Entropy Loss for Numerical Learning of Large Language Models
Zhaohui Zheng, Chenhang He, Shihao Wang +3
Number prediction stands as a fundamental capability of large language models (LLMs) in mathematical problem-solving and code generation. The widely adopted maximum likelihood esti…
Zone Evaluation: Revealing Spatial Bias in Object Detection
Zhaohui Zheng, Yuming Chen, Qibin Hou +3
A fundamental limitation of object detectors is that they suffer from "spatial bias", and in particular perform less satisfactorily when detecting objects near image borders. For a…
CrossKD: Cross-Head Knowledge Distillation for Object Detection
Jiabao Wang, Yuming Chen, Zhaohui Zheng +3
Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object de…
Large Selective Kernel Network for Remote Sensing Object Detection
Yuxuan Li, Qibin Hou, Zhaohui Zheng +3
Recent research on remote sensing object detection has largely focused on improving the representation of oriented bounding boxes but has overlooked the unique prior knowledge pres…
Towards Spatial Equilibrium Object Detection
Zhaohui Zheng, Yuming Chen, Qibin Hou +2
Semantic objects are unevenly distributed over images. In this paper, we study the spatial disequilibrium problem of modern object detectors and propose to quantify this ``spatial…
Localization Distillation for Object Detection
Zhaohui Zheng, Rongguang Ye, Qibin Hou +4
Previous knowledge distillation (KD) methods for object detection mostly focus on feature imitation instead of mimicking the prediction logits due to its inefficiency in distilling…
Localization Distillation for Dense Object Detection
Zhaohui Zheng, Rongguang Ye, Ping Wang +4
Knowledge distillation (KD) has witnessed its powerful capability in learning compact models in object detection. Previous KD methods for object detection mostly focus on imitating…
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation
Zhaohui Zheng, Ping Wang, Dongwei Ren +4
Deep learning-based object detection and instance segmentation have achieved unprecedented progress. In this paper, we propose Complete-IoU (CIoU) loss and Cluster-NMS for enhancin…
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Zhaohui Zheng, Ping Wang, Wei Liu +3
Bounding box regression is the crucial step in object detection. In existing methods, while -norm loss is widely adopted for bounding box regression, it is not tailored to…