31 citations · 33 across the 16 of their papers we have counts for
18 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…
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…
LLaDA-VLA: Vision Language Diffusion Action Models
Yuqing Wen, Hebei Li, Kefan Gu +3
The rapid progress of auto-regressive vision-language models (VLMs) has inspired growing interest in vision-language-action models (VLA) for robotic manipulation. Recently, masked…
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…
FACM: Flow-Anchored Consistency Models
Yansong Peng, Kai Zhu, Yu Liu +4
Continuous-time Consistency Models (CMs) promise efficient few-step generation but face significant challenges with training instability. We argue this instability stems from a fun…
Create Anything Anywhere: Layout-Controllable Personalized Diffusion Model for Multiple Subjects
Wei Li, Hebei Li, Yansong Peng +3
Diffusion models have significantly advanced text-to-image generation, laying the foundation for the development of personalized generative frameworks. However, existing methods la…
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…
COSMIC: Clique-Oriented Semantic Multi-space Integration for Robust CLIP Test-Time Adaptation
Fanding Huang, Jingyan Jiang, Qinting Jiang +3
Recent vision-language models (VLMs) face significant challenges in test-time adaptation to novel domains. While cache-based methods show promise by leveraging historical informati…
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…
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model
Feipeng Ma, Yizhou Zhou, Zheyu Zhang +7
Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated satisfactory performance across various vision-language tasks. Current approaches for vision and l…
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…
Event-assisted Low-Light Video Object Segmentation
Hebei Li, Jin Wang, Jiahui Yuan +6
In the realm of video object segmentation (VOS), the challenge of operating under low-light conditions persists, resulting in notably degraded image quality and compromised accurac…
Scene Adaptive Sparse Transformer for Event-based Object Detection
Yansong Peng, Hebei Li, Yueyi Zhang +2
While recent Transformer-based approaches have shown impressive performances on event-based object detection tasks, their high computational costs still diminish the low power cons…
Deep Multi-Threshold Spiking-UNet for Image Processing
Hebei Li, Yueyi Zhang, Zhiwei Xiong +1
U-Net, known for its simple yet efficient architecture, is widely utilized for image processing tasks and is particularly suitable for deployment on neuromorphic chips. This paper…