Search Results for author:
Found 14 papers, 3 papers with code
Delving into the Trajectory Long-tail Distribution for Muti-object Tracking
In this study, we pioneer an exploration into the distribution patterns of tracking data and identify a pronounced long-tail distribution issue within existing MOT datasets.
Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
The reasoning performance of Large Language Models (LLMs) on a wide range of problems critically relies on chain-of-thought prompting, which involves providing a few chain of thought demonstrations as exemplars in prompts.
Language-Guided Diffusion Model for Visual Grounding
Specifically, we propose a language-guided diffusion framework for visual grounding, LG-DVG, which trains the model to progressively reason queried object boxes by denoising a set of noisy boxes with the language guide.
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
Inspired by their work, we investigate the theoretical guarantees of optimistic online mirror descent (OMD) for the SEA model.
Multi-Modal Dynamic Graph Transformer for Visual Grounding
We found that existing VG methods are trapped by the single-stage grounding process that performs a sole evaluate-and- rank for meticulously prepared regions.
Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation
In this paper, we point out that this issue can be addressed by balancing information flow from the initial model and training dataset to the local adaptation.
Ammonia-induced Calcium Phosphate Nanostructure: A Potential Assay for Studying Osteoporosis and Bone Metastasis
To demon-strate the application in studying bone metastasis, we delivered PC3 prostate cancer conditioned medium and confirmed that both the differentiation of monocytes into osteoclasts and the osteoclastic resorption of the calcium phosphate coating were significantly enhanced.
An Optimized H.266/VVC Software Decoder On Mobile Platform
As the successor of H. 265/HEVC, the new versatile video coding standard (H. 266/VVC) can provide up to 50% bitrate saving with the same subjective quality, at the cost of increased decoding complexity.
2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection
A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons.
1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation
We proposed a one-stage, anchor-free and NMS-free 3D point cloud object detector AFDet, using object key-points to encode the 3D attributes, and to learn an end-to-end point cloud object detection without the need of hand-engineering or learning the anchors.
1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking
This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges.
AFDet: Anchor Free One Stage 3D Object Detection
High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving.
Structured Bayesian Compression for Deep models in mobile enabled devices for connected healthcare
Deep Models, typically Deep neural networks, have millions of parameters, analyze medical data accurately, yet in a time-consuming method.
FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval
The Localization of the target object for data retrieval is a key issue in the Intelligent and Connected Transportation Systems (ICTS).
