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Found 7 papers, 4 papers with code
Multi-attention Associate Prediction Network for Visual Tracking
They are capable of fully capturing the category-related semantics for classification and the local spatial contexts for regression, respectively.
Refining Pre-Trained Motion Models
In the first stage, we use the pre-trained model to estimate motion in a video, and then select the subset of motion estimates which we can verify with cycle-consistency.
Revisiting Deformable Convolution for Depth Completion
Our study reveals that, different from prior work, deformable convolution needs to be applied on an estimated depth map with a relatively high density for better performance.
Pruning for Better Domain Generalizability
On DomainBed benchmark and state-of-the-art MIRO, we can further boost its performance by 1 point only by introducing 10% sparsity into the model.
DiSparse: Disentangled Sparsification for Multitask Model Compression
We analyzed the pruning masks generated with DiSparse and observed strikingly similar sparse network architecture identified by each task even before the training starts.
Updatable Siamese Tracker with Two-stage One-shot Learning
Offline Siamese networks have achieved very promising tracking performance, especially in accuracy and efficiency.
Select Good Regions for Deblurring based on Convolutional Neural Networks
The goal of blind image deblurring is to recover sharp image from one input blurred image with an unknown blur kernel.
