Search Results for author:
Found 14 papers, 9 papers with code
AD-H: Autonomous Driving with Hierarchical Agents
However, prevalent approaches often directly translate high-level instructions into low-level vehicle control signals, which deviates from the inherent language generation paradigm of MLLMs and fails to fully harness their emergent powers.
PP-MobileSeg: Explore the Fast and Accurate Semantic Segmentation Model on Mobile Devices
To address this issue, we propose PP-MobileSeg, a semantic segmentation model that achieves state-of-the-art performance on mobile devices.
Exploring the Relationship Between Architectural Design and Adversarially Robust Generalization
In particular, we comprehensively evaluated 20 most representative adversarially trained architectures on ImageNette and CIFAR-10 datasets towards multiple l_p-norm adversarial attacks.
RAIS: Robust and Accurate Interactive Segmentation via Continual Learning
Interactive image segmentation aims at segmenting a target region through a way of human-computer interaction.
EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle
In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks.
Exploring the Relationship between Architecture and Adversarially Robust Generalization
Inparticular, we comprehensively evaluated 20 most representative adversarially trained architectures on ImageNette and CIFAR-10 datasets towards multiple `p-norm adversarial attacks.
PP-Matting: High-Accuracy Natural Image Matting
Also, we propose a semantic context branch (SCB) that adopts a semantic segmentation subtask.
Ranked #4 on
Image Matting
on Distinctions-646
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
Real-world applications have high demands for semantic segmentation methods.
Ranked #6 on
Real-Time Semantic Segmentation
on Cityscapes test
PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset
This work is the first to construct a large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K fine-labeled frames and extensions to multi-camera teleconferencing.
EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow
In addition, with the proposed method, we develop an efficient interactive segmentation tool for practical data annotation tasks.
Ranked #2 on
Interactive Segmentation
on PASCAL VOC
(NoC@85 metric)
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
Thus, we propose RobustART, the first comprehensive Robustness investigation benchmark on ImageNet regarding ARchitecture design (49 human-designed off-the-shelf architectures and 1200+ networks from neural architecture search) and Training techniques (10+ techniques, e. g., data augmentation) towards diverse noises (adversarial, natural, and system noises).
Unsupervised domain adaptation via coarse-to-fine feature alignment method using contrastive learning
It draws class-wise features closer than coarse feature alignment or class-wise feature alignment only, therefore improves the model's performance to a great extent.
Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
Deep learning models are vulnerable to adversarial examples.
Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization
In this paper, we observe that different $\ell_p$ bounded adversarial perturbations induce different statistical properties that can be separated and characterized by the statistics of Batch Normalization (BN).
