Search Results for author:
Found 33 papers, 19 papers with code
DiffusionAtlas: High-Fidelity Consistent Diffusion Video Editing
Despite the success in image editing, diffusion models still encounter significant hindrances when it comes to video editing due to the challenge of maintaining spatiotemporal consistency in the object's appearance across frames.
Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction
State-of-the-art single-view 360-degree room layout reconstruction methods formulate the problem as a high-level 1D (per-column) regression task.
Hashing Neural Video Decomposition with Multiplicative Residuals in Space-Time
We present a video decomposition method that facilitates layer-based editing of videos with spatiotemporally varying lighting and motion effects.
Shape-Guided: Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
We present a shape-guided expert-learning framework to tackle the problem of unsupervised 3D anomaly detection.
Ranked #1 on
3D Anomaly Detection and Segmentation
on MVTEC 3D-AD
3D Anomaly Detection
3D Anomaly Detection and Segmentation
+2
Multiview Regenerative Morphing with Dual Flows
This paper aims to address a new task of image morphing under a multiview setting, which takes two sets of multiview images as the input and generates intermediate renderings that not only exhibit smooth transitions between the two input sets but also ensure visual consistency across different views at any transition state.
Mask2Hand: Learning to Predict the 3D Hand Pose and Shape from Shadow
We present a self-trainable method, Mask2Hand, which learns to solve the challenging task of predicting 3D hand pose and shape from a 2D binary mask of hand silhouette/shadow without additional manually-annotated data.
Self-supervised 360$^{\circ}$ Room Layout Estimation
We present the first self-supervised method to train panoramic room layout estimation models without any labeled data.
Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction
We present a pose adaptive few-shot learning procedure and a two-stage data interpolation regularization, termed Pose Adaptive Dual Mixup (PADMix), for single-image 3D reconstruction.
Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction
Finally, evaluation on five inward-facing benchmarks shows that our method matches, if not surpasses, NeRF's quality, yet it only takes about 15 minutes to train from scratch for a new scene.
Specialize and Fuse: Pyramidal Output Representation for Semantic Segmentation
We present a novel pyramidal output representation to ensure parsimony with our "specialize and fuse" process for semantic segmentation.
Indoor Panorama Planar 3D Reconstruction via Divide and Conquer
Indoor panorama typically consists of human-made structures parallel or perpendicular to gravity.
Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panorama
We present Omnidirectional Neural Radiance Fields (OmniNeRF), the first method to the application of parallax-enabled novel panoramic view synthesis.
DropLoss for Long-Tail Instance Segmentation
Based on this insight, we develop DropLoss -- a novel adaptive loss to compensate for this imbalance without a trade-off between rare and frequent categories.
HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features
We present HoHoNet, a versatile and efficient framework for holistic understanding of an indoor 360-degree panorama using a Latent Horizontal Feature (LHFeat).
3D Room Layouts From A Single RGB Panorama
Depth Estimation
+1
Learning Camera-Aware Noise Models
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications.
Learning Gaussian Instance Segmentation in Point Clouds
This paper presents a novel method for instance segmentation of 3D point clouds.
Ranked #9 on
3D Instance Segmentation
on S3DIS
(mPrec metric)
Silhouette-Net: 3D Hand Pose Estimation from Silhouettes
3D hand pose estimation has received a lot of attention for its wide range of applications and has made great progress owing to the development of deep learning.
One-Shot Object Detection with Co-Attention and Co-Excitation
This paper aims to tackle the challenging problem of one-shot object detection.
Ranked #3 on
One-Shot Object Detection
on MS COCO
Flat2Layout: Flat Representation for Estimating Layout of General Room Types
This paper also constructs a benchmark for validating the performance on general layout topologies, where Flat2Layout achieves good performance on general room types.
COCO-GAN: Conditional Coordinate Generative Adversarial Network
The fact that the patch generation process is independent to each other inspires a wide range of new applications: firstly, "Patch-Inspired Image Generation" enables us to generate the entire image based on a single patch.
Instance-Level Meta Normalization
This paper presents a normalization mechanism called Instance-Level Meta Normalization (ILM~Norm) to address a learning-to-normalize problem.
C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning
This paper describes a channel-selection approach for simplifying deep neural networks.
Point-to-Point Video Generation
We introduce point-to-point video generation that controls the generation process with two control points: the targeted start- and end-frames.
COCO-GAN: Generation by Parts via Conditional Coordinating
On the computation side, COCO-GAN has a built-in divide-and-conquer paradigm that reduces memory requisition during training and inference, provides high-parallelism, and can generate parts of images on-demand.
Ranked #1 on
Image Generation
on CelebA-HQ 64x64
Bridging the Gap Between Computational Photography and Visual Recognition
From the observed results, it is evident that we are in the early days of building a bridge between computational photography and visual recognition, leaving many opportunities for innovation in this area.
HorizonNet: Learning Room Layout with 1D Representation and Pano Stretch Data Augmentation
We present a new approach to the problem of estimating the 3D room layout from a single panoramic image.
3D Room Layouts From A Single RGB Panorama
Data Augmentation
Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects
This paper presents a "learning to learn" approach to figure-ground image segmentation.
SwipeCut: Interactive Segmentation with Diversified Seed Proposals
At each round of interaction the user is only presented with a small number of informative query seeds that are far apart from each other.
Non-local RoI for Cross-Object Perception
We present a generic and flexible module that encodes region proposals by both their intrinsic features and the extrinsic correlations to the others.
Escaping from Collapsing Modes in a Constrained Space
Generative adversarial networks (GANs) often suffer from unpredictable mode-collapsing during training.
Ranked #29 on
Image Generation
on CelebA 64x64
Non-local RoIs for Instance Segmentation
We introduce the concept of Non-Local RoI (NL-RoI) Block as a generic and flexible module that can be seamlessly adapted into different Mask R-CNN heads for various tasks.
Self Adversarial Training for Human Pose Estimation
This paper presents a deep learning based approach to the problem of human pose estimation.
Ranked #5 on
Pose Estimation
on Leeds Sports Poses
Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative Study
Automatic photo cropping is an important tool for improving visual quality of digital photos without resorting to tedious manual selection.
