31 citations · 31 across the 13 of their papers we have counts for
16 papers
RiO-DETRv2: Geometry-Aware Uncertainty Modeling Meets Real-Time Oriented Object Detection Transformer
Zhangchi Hu, Zilong He, Yifan Zhao +6
RiO-DETR is the first real-time end-to-end transformer for oriented object detection, yet further localization gains require a more expressive box representation. Although distribu…
VaME: Exploring Variational Latent Reasoning for Multimodal Embeddings
Peixi Wu, Mingzhou Jiang, Feipeng Ma +11
Universal multimodal retrieval requires compact embeddings that preserve task-relevant semantic information across diverse modalities. Prior works have incorporated latent reasonin…
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding?
Yun Li, Biao Yang, Peixi Wu +5
Embeddings have emerged as a standard representational interface linking foundation models with downstream systems. Most embedding benchmarks assess representations through discrim…
LaME: Learning to Think in Latent Space for Multimodal Embedding via Information Bottleneck
Peixi Wu, Biao Yang, Feipeng Ma +7
Reasoning-driven universal multimodal embedding has advanced rapidly by introducing Chain-of-Thought (CoT) reasoning into the embedding pipeline. Despite the strong performance acr…
Beyond Chain-of-Thought: Rewrite as a Universal Interface for Generative Multimodal Embeddings
Peixi Wu, Ke Mei, Feipeng Ma +15
Multimodal Large Language Models (MLLMs) have emerged as a promising foundation for universal multimodal embeddings. Recent studies have shown that reasoning-driven generative mult…
RiO-DETR: DETR for Real-time Oriented Object Detection
Zhangchi Hu, Yifan Zhao, Yansong Peng +8
We present RiO-DETR: DETR for Real-time Oriented Object Detection, the first real-time oriented detection transformer to the best of our knowledge. Adapting DETR to oriented boundi…
DASH: 4D Hash Encoding with Self-Supervised Decomposition for Real-Time Dynamic Scene Rendering
Jie Chen, Zhangchi Hu, Peixi Wu +3
Dynamic scene reconstruction is a long-term challenge in 3D vision. Existing plane-based methods in dynamic Gaussian splatting suffer from an unsuitable low-rank assumption, causin…
Efficient Event-Based Semantic Segmentation via Exploiting Frame-Event Fusion: A Hybrid Neural Network Approach
Hebei Li, Yansong Peng, Jiahui Yuan +4
Event cameras have recently been introduced into image semantic segmentation, owing to their high temporal resolution and other advantageous properties. However, existing event-bas…
SVL: Empowering Spiking Neural Networks for Efficient 3D Open-World Understanding
Xuerui Qiu, Peixi Wu, Yaozhi Wen +5
Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing SNNs still exhibit a significant performance gap compared t…
Dome-DETR: DETR with Density-Oriented Feature-Query Manipulation for Efficient Tiny Object Detection
Zhangchi Hu, Peixi Wu, Jie Chen +5
Tiny object detection plays a vital role in drone surveillance, remote sensing, and autonomous systems, enabling the identification of small targets across vast landscapes. However…
Efficient Spiking Point Mamba for Point Cloud Analysis
Peixi Wu, Bosong Chai, Menghua Zheng +6
Bio-inspired Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing 3D SNNs have struggled with long-range depende…
Spiking Point Transformer for Point Cloud Classification
Peixi Wu, Bosong Chai, Hebei Li +6
Spiking Neural Networks (SNNs) offer an attractive and energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their sparse binary activation. When SN…
D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement
Yansong Peng, Hebei Li, Peixi Wu +3
We introduce D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE com…
Enhanced Object Detection: A Study on Vast Vocabulary Object Detection Track for V3Det Challenge 2024
Peixi Wu, Bosong Chai, Xuan Nie +6
In this technical report, we present our findings from the research conducted on the Vast Vocabulary Visual Detection (V3Det) dataset for Supervised Vast Vocabulary Visual Detectio…
V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results
Jiaqi Wang, Yuhang Zang, Pan Zhang +31
Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown…
LIO-PPF: Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
Xingyu Chen, Peixi Wu, Ge Li +1
As a crucial infrastructure of intelligent mobile robots, LiDAR-Inertial odometry (LIO) provides the basic capability of state estimation by tracking LiDAR scans. The high-accuracy…