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Found 10 papers, 3 papers with code
Bridging the Semantic-Numerical Gap: A Numerical Reasoning Method of Cross-modal Knowledge Graph for Material Property Prediction
In this paper, we propose a numerical reasoning method for material KGs (NR-KG), which constructs a cross-modal KG using semantic nodes and numerical proxy nodes.
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception
To further capture human characteristics, we propose a structure-invariant alignment loss that enforces different masked views, guided by the human part prior, to be closely aligned for the same image.
MM-NeRF: Multimodal-Guided 3D Multi-Style Transfer of Neural Radiance Field
3D style transfer aims to generate stylized views of 3D scenes with specified styles, which requires high-quality generating and keeping multi-view consistency.
Learning Structure-Guided Diffusion Model for 2D Human Pose Estimation
One of the mainstream schemes for 2D human pose estimation (HPE) is learning keypoints heatmaps by a neural network.
PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers
To handle the variances of objects as time proceeds, a novel scheme of progressive decoding is used to update pose and shape queries at each frame.
Ranked #23 on
3D Human Pose Estimation
on 3DPW
Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-Resolution
Video Super-Resolution (VSR) aims to restore high-resolution (HR) videos from low-resolution (LR) videos.
Ranked #2 on
Video Super-Resolution
on REDS4- 4x upscaling
Weakly-supervised Pre-training for 3D Human Pose Estimation via Perspective Knowledge
Based on MCPC, we propose a weakly-supervised pre-training (WSP) strategy to distinguish the depth relationship between two points in an image.
IVT: An End-to-End Instance-guided Video Transformer for 3D Pose Estimation
In particular, we firstly formulate video frames as a series of instance-guided tokens and each token is in charge of predicting the 3D pose of a human instance.
Ranked #10 on
3D Multi-Person Pose Estimation
on Panoptic
(using extra training data)
Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution
First, we divide a video frame into patches, and transform each patch into DCT spectral maps in which each channel represents a frequency band.
Ranked #3 on
Video Super-Resolution
on REDS4- 4x upscaling
Dynamic Graph Reasoning for Multi-person 3D Pose Estimation
Finally, the 3D poses are decoded according to dynamic decoding graphs for each detected person.
3D Multi-Person Pose Estimation (absolute)
3D Multi-Person Pose Estimation (root-relative)
+1
