120 citations · 363 across the 20 of their papers we have counts for
11 papers · 1 filter
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…