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Found 13 papers, 6 papers with code
Feature Compression for Cloud-Edge Multimodal 3D Object Detection
Given a sparse tensor-based object detection network at the edge device, we introduce two modes to accommodate different application requirements: Transmission-Friendly Feature Compression (T-FFC) and Accuracy-Friendly Feature Compression (A-FFC).
MeshSegmenter: Zero-Shot Mesh Semantic Segmentation via Texture Synthesis
Specifically, our model leverages the Segment Anything Model (SAM) model to segment the target regions from images rendered from the 3D shape.
The Third Monocular Depth Estimation Challenge
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC).
MLLM-Tool: A Multimodal Large Language Model For Tool Agent Learning
Recently, the astonishing performance of large language models (LLMs) in natural language comprehension and generation tasks triggered lots of exploration of using them as central controllers to build agent systems.
TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding
Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc.
P$^2$SDF for Neural Indoor Scene Reconstruction
As the unsupervised plane segments are usually noisy and inaccurate, we propose to assign different weights to the sampled points on the plane in plane estimation as well as the regularization loss.
TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting
Existing methods focus on performing repetitive action counting in short videos, which is tough for dealing with longer videos in more realistic scenarios.
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Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images
To mitigate this problem, in this paper, we propose a novel Proxy-bridged Image Reconstruction Network (ProxyAno) for anomaly detection in medical images.
OH-Former: Omni-Relational High-Order Transformer for Person Re-Identification
Transformers have shown preferable performance on many vision tasks.
Crowd Counting With Partial Annotations in an Image
To fully leverage the data captured from different scenes with different view angles while reducing the annotation cost, this paper studies a novel crowd counting setting, i. e. only using partial annotations in each image as training data.
Sparse PCA via $l_{2,p}$-Norm Regularization for Unsupervised Feature Selection
However, real-world data contain a large number of noise samples and features, making the similarity matrix constructed by original data cannot be completely reliable.
Exact Indexing of Time Series under Dynamic Time Warping
Unfortunately, there is still a lack of an effective lower bounding distance that can measure unequal-length time series and has desirable tightness.
PPGNet: Learning Point-Pair Graph for Line Segment Detection
In this paper, we present a novel framework to detect line segments in man-made environments.
