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20162023
most citedTransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification

506 citations · 716 across the 28 of their papers we have counts for

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25 papers · 1 filter

cs.CV20232 cited

CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction

Yan Di, Chenyangguang Zhang, Pengyuan Wang +6

In this paper, we present a novel shape reconstruction method leveraging diffusion model to generate 3D sparse point cloud for the object captured in a single RGB image. Recent met…

cs.CV20237 cited

DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field

Chenyangguang Zhang, Yan Di, Ruida Zhang +4

Reconstructing hand-held objects from a single RGB image is an important and challenging problem. Existing works utilizing Signed Distance Fields (SDF) reveal limitations in compre…

cs.CV202360 cited

Guided Depth Map Super-resolution: A Survey

Zhiwei Zhong, Xianming Liu, Junjun Jiang +2

Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution (HR) depth map from a low-resolution (LR) observation with the help of a paired HR color image…

cs.CV20224 cited

Learning to Annotate Part Segmentation with Gradient Matching

Yu Yang, Xiaotian Cheng, Hakan Bilen +1

The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate.…

cs.CV202222 cited

Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation

Jialei Xu, Xianming Liu, Yuanchao Bai +4

Depth map estimation from images is an important task in robotic systems. Existing methods can be categorized into two groups including multi-view stereo and monocular depth estima…

cs.CV20225 cited

Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

Wenbo Zhao, Xianming Liu, Zhiwei Zhong +4

Point clouds upsampling is a challenging issue to generate dense and uniform point clouds from the given sparse input. Most existing methods either take the end-to-end supervised l…