5 citations · 14 across the 20 of their papers we have counts for
22 papers
Feat2Go: Visual Feature-Grounded Value Estimation for Embodied Reinforcement Learning
Junyang Shu, Zhiwei Lin, Bingqing Wei +1
Reinforcement learning is a promising approach for improving the capabilities of vision-language-action (VLA) models while avoiding the heavy data requirements of imitation learnin…
VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection
Chih-Chung Liu, Zhiwei Lin, Yongtao Wang
Open-world object detection aims to localize and recognize objects beyond a fixed closed-set label space. It is commonly divided into two categories, i.e., open-vocabulary detectio…
QAPruner: Quantization-Aware Vision Token Pruning for Multimodal Large Language Models
Xinhao Wang, Zhonyu Xia, Zhiwei Lin +2
Multimodal Large Language Models (MLLMs) have shown strong reasoning ability, but their high computational and memory costs hinder deployment in resource-constrained settings. Whil…
ELITE: Experiential Learning and Intent-Aware Transfer for Self-improving Embodied Agents
Bingqing Wei, Zhongyu Xia, Dingai Liu +3
Vision-language models (VLMs) have shown remarkable general capabilities, yet embodied agents built on them fail at complex tasks, often skipping critical steps, proposing invalid…
CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search
Zhe Li, Zhiwei Lin, Yongtao Wang
The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of neural architectures. However, m…
Multi-Representation Adapter with Neural Architecture Search for Efficient Range-Doppler Radar Object Detection
Zhiwei Lin, Weicheng Zheng, Yongtao Wang
Detecting objects efficiently from radar sensors has recently become a popular trend due to their robustness against adverse lighting and weather conditions compared with cameras.…
SAR-NAS: Lightweight SAR Object Detection with Neural Architecture Search
Xinyi Yu, Zhiwei Lin, Yongtao Wang
Synthetic Aperture Radar (SAR) object detection faces significant challenges from speckle noise, small target ambiguities, and on-board computational constraints. While existing ap…
PTQAT: A Hybrid Parameter-Efficient Quantization Algorithm for 3D Perception Tasks
Xinhao Wang, Zhiwei Lin, Zhongyu Xia +1
Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) represent two mainstream model quantization approaches. However, PTQ often leads to unacceptable performance…
RegCL: Compact Continual SAM Adaptation for Visual Grounding in Multi-Sensorial Media
Yuan-Chen Shu, Zhiwei Lin, Xiaoyu Zhou +1
Multi-sensorial media systems, including AR/VR, remote operation, and embodied AI, require visual grounding modules that remain reliable as sensing environments and application dom…
RFTF: Reinforcement Fine-tuning for Embodied Agents with Temporal Feedback
Junyang Shu, Zhiwei Lin, Yongtao Wang
Vision-Language-Action (VLA) models have demonstrated significant potential in the field of embodied intelligence, enabling agents to follow human instructions to complete complex…
VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion
Zhiwei Lin, Yongtao Wang
Current perception models have achieved remarkable success by leveraging large-scale labeled datasets, but still face challenges in open-world environments with novel objects. To a…
RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection
Jingtong Yue, Zhiwei Lin, Xin Lin +5
While recent low-cost radar-camera approaches have shown promising results in multi-modal 3D object detection, both sensors face challenges from environmental and intrinsic disturb…
AutoOcc: Automatic Open-Ended Semantic Occupancy Annotation via Vision-Language Guided Gaussian Splatting
Xiaoyu Zhou, Jingqi Wang, Yongtao Wang +3
Obtaining high-quality 3D semantic occupancy from raw sensor data remains an essential yet challenging task, often requiring extensive manual labeling. In this work, we propose Aut…
OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection
Zhongyu Xia, Jishuo Li, Zhiwei Lin +3
Open-world perception aims to develop a model adaptable to novel domains and various sensor configurations and can understand uncommon objects and corner cases. However, current re…
TEOcc: Radar-camera Multi-modal Occupancy Prediction via Temporal Enhancement
Zhiwei Lin, Hongbo Jin, Yongtao Wang +2
As a novel 3D scene representation, semantic occupancy has gained much attention in autonomous driving. However, existing occupancy prediction methods mainly focus on designing bet…
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts
Zhiwei Lin, Yongtao Wang, Zhi Tang
Existing perception models achieve great success by learning from large amounts of labeled data, but they still struggle with open-world scenarios. To alleviate this issue, researc…
RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network
Zhiwei Lin, Zhe Liu, Yongtao Wang +2
Perceiving the surrounding environment is a fundamental task in autonomous driving. To obtain highly accurate perception results, modern autonomous driving systems typically employ…
HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras
Zhongyu Xia, ZhiWei Lin, Xinhao Wang +5
Three-dimensional perception from multi-view cameras is a crucial component in autonomous driving systems, which involves multiple tasks like 3D object detection and bird's-eye-vie…
RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection
Zhiwei Lin, Zhe Liu, Zhongyu Xia +7
Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce costs in practice, low-cost multi-view cameras for 3D object detection are proposed to r…
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong +5
We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate…
DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes
Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan +3
We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially an…
SAMPLING: Scene-adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image
Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan +3
Recent novel view synthesis methods obtain promising results for relatively small scenes, e.g., indoor environments and scenes with a few objects, but tend to fail for unbounded ou…