• Publications
  • Influence
Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding
  • Z. He, J. Cai, C. Chen
  • Computer Science
  • IEEE Trans. Circuits Syst. Video Technol.
  • 1 June 2002
We first develop a rate-distortion (R-D) model for DCT-based video coding incorporating the macroblock (MB) intra refreshing rate. For any given bit rate and intra refreshing rate, this model isExpand
  • 384
  • 43
  • Open Access
Weakly-Supervised 3D Hand Pose Estimation from Monocular RGB Images
Compared with depth-based 3D hand pose estimation, it is more challenging to infer 3D hand pose from monocular RGB images, due to substantial depth ambiguity and the difficulty of obtainingExpand
  • 94
  • 19
  • Open Access
Pluralistic Image Completion
Most image completion methods produce only one result for each masked input, although there may be many reasonable possibilities. In this paper, we present an approach for pluralistic imageExpand
  • 54
  • 18
  • Open Access
3D Hand Shape and Pose Estimation From a Single RGB Image
This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image. Most current methods in 3D hand analysis from monocular RGB images onlyExpand
  • 83
  • 17
  • Open Access
Robust Interactive Image Segmentation Using Convex Active Contours
The state-of-the-art interactive image segmentation algorithms are sensitive to the user inputs and often unable to produce an accurate boundary with a small amount of user interaction. TheyExpand
  • 109
  • 14
  • Open Access
User-Friendly Interactive Image Segmentation Through Unified Combinatorial User Inputs
One weakness in the existing interactive image segmentation algorithms is the lack of more intelligent ways to understand the intention of user inputs. In this paper, we advocate the use of multipleExpand
  • 138
  • 13
  • Open Access
Image Co-segmentation via Saliency Co-fusion
Most existing high-performance co-segmentation algorithms are usually complex due to the way of co-labeling a set of images as well as the common need of fine-tuning few parameters for effectiveExpand
  • 71
  • 12
  • Open Access
T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks
Current methods for single-image depth estimation use training datasets with real image-depth pairs or stereo pairs, which are not easy to acquire. We propose a framework, trained on syntheticExpand
  • 52
  • 12
  • Open Access
Large-Margin Multi-Modal Deep Learning for RGB-D Object Recognition
Most existing feature learning-based methods for RGB-D object recognition either combine RGB and depth data in an undifferentiated manner from the outset, or learn features from color and depthExpand
  • 95
  • 10
Auto-Encoding Scene Graphs for Image Captioning
We propose Scene Graph Auto-Encoder (SGAE) that incorporates the language inductive bias into the encoder-decoder image captioning framework for more human-like captions. Intuitively, we humans useExpand
  • 101
  • 10
  • Open Access