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04/17/2023
MoDA: Modeling Deformable 3D Objects from Casual Videos
In this paper, we focus on the challenges of modeling deformable 3D obje...
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01/18/2023
Effective End-to-End Vision Language Pretraining with Semantic Visual Loss
Current vision language pretraining models are dominated by methods usin...
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11/18/2022
Unsupervised 3D Pose Transfer with Cross Consistency and Dual Reconstruction
The goal of 3D pose transfer is to transfer the pose from the source mes...
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08/23/2022
CRCNet: Few-shot Segmentation with Cross-Reference and Region-Global Conditional Networks
Few-shot segmentation aims to learn a segmentation model that can be gen...
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08/10/2022
RWSeg: Cross-graph Competing Random Walks for Weakly Supervised 3D Instance Segmentation
Instance segmentation on 3D point clouds has been attracting increasing ...
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01/06/2022
Self-Training Vision Language BERTs with a Unified Conditional Model
Natural language BERTs are trained with language corpus in a self-superv...
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12/11/2021
On Automatic Data Augmentation for 3D Point Cloud Classification
Data augmentation is an important technique to reduce overfitting and im...
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11/09/2021
On Representation Knowledge Distillation for Graph Neural Networks
Knowledge distillation is a promising learning paradigm for boosting the...
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09/30/2021
3D Pose Transfer with Correspondence Learning and Mesh Refinement
3D pose transfer is one of the most challenging 3D generation tasks. It ...
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08/11/2021
Few-Shot Segmentation with Global and Local Contrastive Learning
In this work, we address the challenging task of few-shot segmentation. ...
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08/04/2021
Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds
Recently deep learning has achieved significant progress on point cloud ...
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07/23/2021
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds
Semantic segmentation on 3D point clouds is an important task for 3D sce...
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05/17/2021
HCRF-Flow: Scene Flow from Point Clouds with Continuous High-order CRFs and Position-aware Flow Embedding
Scene flow in 3D point clouds plays an important role in understanding d...
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09/21/2020
Feature Flow: In-network Feature Flow Estimation for Video Object Detection
Optical flow, which expresses pixel displacement, is widely used in many...
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03/24/2020
CRNet: Cross-Reference Networks for Few-Shot Segmentation
Over the past few years, state-of-the-art image segmentation algorithms ...
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03/21/2019
Towards Robust Curve Text Detection with Conditional Spatial Expansion
It is challenging to detect curve texts due to their irregular shapes an...
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03/06/2019
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning
Recent progress in semantic segmentation is driven by deep Convolutional...
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09/30/2018
Correlation Propagation Networks for Scene Text Detection
In this work, we propose a novel hybrid method for scene text detection ...
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03/26/2017
Structured Learning of Tree Potentials in CRF for Image Segmentation
We propose a new approach to image segmentation, which exploits the adva...
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01/28/2016
Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss
Recent works on deep conditional random fields (CRF) have set new record...
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03/28/2015
CRF Learning with CNN Features for Image Segmentation
Conditional Random Rields (CRF) have been widely applied in image segmen...
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02/26/2015
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
In this article, we tackle the problem of depth estimation from single m...
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11/24/2014
Deep Convolutional Neural Fields for Depth Estimation from a Single Image
We consider the problem of depth estimation from a single monocular imag...
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01/04/2014
From Kernel Machines to Ensemble Learning
Ensemble methods such as boosting combine multiple learners to obtain be...
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10/07/2013