3 citations · 3 across the 13 of their papers we have counts for
13 papers · 1 filter
VTO: Visual Tool Orchestration for Video Anomaly Detection
Rui Wang, Yeteng Wu, Xianling Zhang +1
Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Traditional deep learning approaches are fundamental…
Boosting Robustness for All-Weather Self-Supervised Depth Estimation in Autonomous Driving
Mengshi Qi, Xiaoyang Bi, Xianlin Zhang +1
Self-supervised depth estimation is challenging for safe autonomous driving under various adverse weather conditions due to sensor perception degradation. These challenges arise fr…
CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving
Zhaohong Liu, Hao Ye, Xianlin Zhang +1
End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers from reasoning hallucinations an…
SGFormer++: Semantic Graph Transformer for Incremental 3D Scene Graph Generation
Mengshi Qi, Changsheng Lv, Zijian Fu +2
In this paper, we propose SGFormer++, a novel Semantic Graph Transformer for 3D scene graph generation (SGG), which aims to parse point cloud scenes into semantic structural graphs…
Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation
Mengshi Qi, Wei Deng, Xianlin Zhang +1
Large Vision-Language Models have achieved significant reasoning performance in various tasks. However, there are few studies on text-to-3D indoor scene generation with LVLMs. The…
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
Wei Deng, Xianlin Zhang, Mengshi Qi
Enabling Vision-Language Models (VLMs) to perform spatial reasoning remains challenging. Existing approaches treat VLMs as passive observers, which is difficult for real-world appl…
Towards Balanced Multi-Modal Learning in 3D Human Pose Estimation
Mengshi Qi, Jiaxuan Peng, Xianlin Zhang +1
3D human pose estimation (3D HPE) has emerged as a prominent research topic, particularly in the realm of RGB-based methods. However, the use of RGB images is often limited by issu…
LiHi-GS: LiDAR-Supervised Gaussian Splatting for Highway Driving Scene Reconstruction
Pou-Chun Kung, Xianling Zhang, Katherine A. Skinner +1
Photorealistic 3D scene reconstruction plays an important role in autonomous driving, enabling the generation of novel data from existing datasets to simulate safety-critical scena…
Unveiling the Ambiguity in Neural Inverse Rendering: A Parameter Compensation Analysis
Georgios Kouros, Minye Wu, Sushruth Nagesh +2
Inverse rendering aims to reconstruct the scene properties of objects solely from multiview images. However, it is an ill-posed problem prone to producing ambiguous estimations dev…
DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within Datasets
Shubham Shrivastava, Xianling Zhang, Sushruth Nagesh +1
Data imbalance is a well-known issue in the field of machine learning, attributable to the cost of data collection, the difficulty of labeling, and the geographical distribution of…
LANe: Lighting-Aware Neural Fields for Compositional Scene Synthesis
Akshay Krishnan, Amit Raj, Xianling Zhang +5
Neural fields have recently enjoyed great success in representing and rendering 3D scenes. However, most state-of-the-art implicit representations model static or dynamic scenes as…
SIMBAR: Single Image-Based Scene Relighting For Effective Data Augmentation For Automated Driving Vision Tasks
Xianling Zhang, Nathan Tseng, Ameerah Syed +2
Real-world autonomous driving datasets comprise of images aggregated from different drives on the road. The ability to relight captured scenes to unseen lighting conditions, in a c…
Deflating Dataset Bias Using Synthetic Data Augmentation
Nikita Jaipuria, Xianling Zhang, Rohan Bhasin +5
Deep Learning has seen an unprecedented increase in vision applications since the publication of large-scale object recognition datasets and introduction of scalable compute hardwa…