120 citations · 363 across the 20 of their papers we have counts for
20 papers
ES3D: Embedding Semantics into 3D Space for Component-Aware Editing
Xuancheng Jin, Rengan Xie, Jiayuan Lu +5
Existing 3D editing methods have made notable progress in controllability, yet they remain limited in several important ways. Most approaches rely on text-driven editing, which str…
DVD: Deterministic Video Depth Estimation with Generative Priors
Hongfei Zhang, Harold Haodong Chen, Chenfei Liao +12
Existing video depth estimation faces a fundamental trade-off: generative models suffer from stochastic geometric hallucinations and scale drift, while discriminative models demand…
Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF
Leheng Li, Qing Lian, Ying-Cong Chen
Deep neural networks (DNNs) have been proven extremely susceptible to adversarial examples, which raises special safety-critical concerns for DNN-based autonomous driving stacks (i…
Dual-Balancing for Multi-Task Learning
Baijiong Lin, Weisen Jiang, Feiyang Ye +6
Multi-task learning aims to learn multiple related tasks simultaneously and has achieved great success in various fields. However, the disparity in loss and gradient scales among t…
High Dynamic Range Image Reconstruction via Deep Explicit Polynomial Curve Estimation
Jiaqi Tang, Xiaogang Xu, Sixing Hu +1
Due to limited camera capacities, digital images usually have a narrower dynamic illumination range than real-world scene radiance. To resolve this problem, High Dynamic Range (HDR…
Not All Steps are Created Equal: Selective Diffusion Distillation for Image Manipulation
Luozhou Wang, Shuai Yang, Shu Liu +1
Conditional diffusion models have demonstrated impressive performance in image manipulation tasks. The general pipeline involves adding noise to the image and then denoising it. Ho…
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
Lingdong Kong, Yaru Niu, Shaoyuan Xie +39
Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical a…
Text-Anchored Score Composition: Tackling Condition Misalignment in Text-to-Image Diffusion Models
Luozhou Wang, Guibao Shen, Wenhang Ge +3
Text-to-image diffusion models have advanced towards more controllable generation via supporting various additional conditions (e.g.,depth map, bounding box) beyond text. However,…
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
Yixun Liang, Hao He, Ying-cong Chen
Generalizable neural surface reconstruction techniques have attracted great attention in recent years. However, they encounter limitations of low confidence depth distribution and…
Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
Leheng Li, Qing Lian, Luozhou Wang +2
This work explores the use of 3D generative models to synthesize training data for 3D vision tasks. The key requirements of the generative models are that the generated data should…
Label Name is Mantra: Unifying Point Cloud Segmentation across Heterogeneous Datasets
Yixun Liang, Hao He, Shishi Xiao +2
Point cloud segmentation is a fundamental task in 3D vision that serves a wide range of applications. Although great progresses have been made these years, its practical usability…
Neuron Structure Modeling for Generalizable Remote Physiological Measurement
Hao Lu, Zitong Yu, Xuesong Niu +1
Remote photoplethysmography (rPPG) technology has drawn increasing attention in recent years. It can extract Blood Volume Pulse (BVP) from facial videos, making many applications l…
Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection
Wenhang Ge, Tao Hu, Haoyu Zhao +2
Neural implicit surface learning has shown significant progress in multi-view 3D reconstruction, where an object is represented by multilayer perceptrons that provide continuous im…
ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions
Anjun Chen, Xiangyu Wang, Kun Shi +6
3D human reconstruction from RGB images achieves decent results in good weather conditions but degrades dramatically in rough weather. Complementary, mmWave radars have been employ…
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations
Yunlong Ran, Jing Zeng, Shibo He +5
Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying t…
Look Before You Leap: Detecting Phishing Web Pages by Exploiting Raw URL And HTML Characteristics
Chidimma Opara, Yingke Chen, Bo. wei
Phishing websites distribute unsolicited content and are frequently used to commit email and internet fraud; detecting them before any user information is submitted is critical. Se…
HTMLPhish: Enabling Phishing Web Page Detection by Applying Deep Learning Techniques on HTML Analysis
Chidimma Opara, Bo Wei, Yingke Chen
Recently, the development and implementation of phishing attacks require little technical skills and costs. This uprising has led to an ever-growing number of phishing attacks on t…
Individual Planning in Agent Populations: Exploiting Anonymity and Frame-Action Hypergraphs
Ekhlas Sonu, Yingke Chen, Prashant Doshi
Interactive partially observable Markov decision processes (I-POMDP) provide a formal framework for planning for a self-interested agent in multiagent settings. An agent operating…
Team Behavior in Interactive Dynamic Influence Diagrams with Applications to Ad Hoc Teams
Muthukumaran Chandrasekaran, Prashant Doshi, Yifeng Zeng +1
Planning for ad hoc teamwork is challenging because it involves agents collaborating without any prior coordination or communication. The focus is on principled methods for a singl…
Learning Markov Decision Processes for Model Checking
Hua Mao, Yingke Chen, Manfred Jaeger +3
Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed…