Semantic Part Detection
3 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Semantic Part Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
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PASCAL-Part
Latest papers with no code
Split, Merge, and Refine: Fitting Tight Bounding Boxes via Over-Segmentation and Iterative Search
We propose a novel framework for finding a set of tight bounding boxes of a 3D shape via over-segmentation and iterative merging and refinement.
Pose-Guided Knowledge Transfer for Object Part Segmentation
Object part segmentation is an important problem for many applications, but generating the annotations to train a part segmentation model is typically quite labor-intensive.
Visual Concepts and Compositional Voting
We use clustering algorithms to study the population activities of the features and extract a set of visual concepts which we show are visually tight and correspond to semantic parts of vehicles.
DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion
The first layer extracts the evidence of local visual cues, and the second layer performs a voting mechanism by utilizing the spatial relationship between visual cues and semantic parts.
Detecting Semantic Parts on Partially Occluded Objects
Our approach detects semantic parts by accumulating the confidence of local visual cues.
Objects as context for detecting their semantic parts
We present a semantic part detection approach that effectively leverages object information. We use the object appearance and its class as indicators of what parts to expect.
SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-Grained Recognition
In this paper, we propose a new CNN architecture that integrates semantic part detection and abstraction (SPDA-CNN) for fine-grained classification.
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts
Our model automatically decouples the holistic object or body parts from the model when they are hard to detect.
