Search Results for author:
Found 26 papers, 11 papers with code
Idea-2-3D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs
The definition of an IDEA is the composition of multimodal inputs including text, image, and 3D models.
Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail
In this paper, we propose a new method called \emph{Ultraman} for fast reconstruction of textured 3D human models from a single image.
AS-FIBA: Adaptive Selective Frequency-Injection for Backdoor Attack on Deep Face Restoration
Extensive experiments demonstrate the efficacy of the degradation objective on state-of-the-art face restoration models.
Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning
3D medical image segmentation is a challenging task with crucial implications for disease diagnosis and treatment planning.
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration
This study delves into the enhancement of Under-Display Camera (UDC) image restoration models, focusing on their robustness against adversarial attacks.
SyncTalk: The Devil is in the Synchronization for Talking Head Synthesis
A lifelike talking head requires synchronized coordination of subject identity, lip movements, facial expressions, and head poses.
BeatDance: A Beat-Based Model-Agnostic Contrastive Learning Framework for Music-Dance Retrieval
Dance and music are closely related forms of expression, with mutual retrieval between dance videos and music being a fundamental task in various fields like education, art, and sports.
STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation
Scene Graph Generation is a critical enabler of environmental comprehension for autonomous robotic systems.
Multi-dimensional Fusion and Consistency for Semi-supervised Medical Image Segmentation
In this paper, we introduce a novel semi-supervised learning framework tailored for medical image segmentation.
D-IF: Uncertainty-aware Human Digitization via Implicit Distribution Field
In this paper, we propose replacing the implicit value with an adaptive uncertainty distribution, to differentiate between points based on their distance to the surface.
Benchmarking Ultra-High-Definition Image Reflection Removal
To the best of our knowledge, these two datasets are the first largest-scale UHD datasets for SIRR.
DenseMP: Unsupervised Dense Pre-training for Few-shot Medical Image Segmentation
Few-shot medical image semantic segmentation is of paramount importance in the domain of medical image analysis.
SelfTalk: A Self-Supervised Commutative Training Diagram to Comprehend 3D Talking Faces
To enhance the visual accuracy of generated lip movement while reducing the dependence on labeled data, we propose a novel framework SelfTalk, by involving self-supervision in a cross-modals network system to learn 3D talking faces.
EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation
Specifically, we introduce the emotion disentangling encoder (EDE) to disentangle the emotion and content in the speech by cross-reconstructed speech signals with different emotion labels.
Robust Single Image Reflection Removal Against Adversarial Attacks
This paper addresses the problem of robust deep single-image reflection removal (SIRR) against adversarial attacks.
Ranked #2 on
Reflection Removal
on Real20
SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Estimation
In stage 1, a novel devices detection and tracking scheme is introduced, which accurately locate the height limit devices in the left or right image.
FuRPE: Learning Full-body Reconstruction from Part Experts
These novel elements of FuRPE not only serve to further refine the model but also to reduce potential biases that may arise from inaccuracies in pseudo labels, thereby optimizing the network's training process and enhancing the robustness of the model.
GIDP: Learning a Good Initialization and Inducing Descriptor Post-enhancing for Large-scale Place Recognition
Large-scale place recognition is a fundamental but challenging task, which plays an increasingly important role in autonomous driving and robotics.
Human Pose Driven Object Effects Recommendation
In this paper, we research the new topic of object effects recommendation in micro-video platforms, which is a challenging but important task for many practical applications such as advertisement insertion.
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object Detection
The insight behind introducing MonoSIM is that we propose to simulate the feature learning behaviors of a point cloud based detector for monocular detector during the training period.
Reconstruction-Aware Prior Distillation for Semi-supervised Point Cloud Completion
Real-world sensors often produce incomplete, irregular, and noisy point clouds, making point cloud completion increasingly important.
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image
Recently, RGBD-based category-level 6D object pose estimation has achieved promising improvement in performance, however, the requirement of depth information prohibits broader applications.
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation
ACR-Pose consists of a Reconstructor and a Discriminator.
RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network
Third, we apply these kernels to previous point cloud features to generate new features, which is the well-known SO(3) mapping process.
Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview
Therefore, this study presents a comprehensive review of recent progress in object pose detection and tracking that belongs to the deep learning technical route.
SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition
Point cloud-based large scale place recognition is fundamental for many applications like Simultaneous Localization and Mapping (SLAM).
Ranked #2 on
3D Place Recognition
on Oxford RobotCar Dataset
