Search Results for author:
Found 7 papers, 4 papers with code
LLM-Powered Explanations: Unraveling Recommendations Through Subgraph Reasoning
Finally, these reasoning paths are fed into the LLMs to generate interpretable explanations of the recommendation results.
SwinRDM: Integrate SwinRNN with Diffusion Model towards High-Resolution and High-Quality Weather Forecasting
Recurrent predictions for future atmospheric fields are firstly performed at 1. 40625-degree resolution, and then a diffusion-based super-resolution model is leveraged to recover the high spatial resolution and finer-scale atmospheric details.
Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions
In this paper, our goal is to design a simple learning paradigm for long-tail visual recognition, which not only improves the robustness of the feature extractor but also alleviates the bias of the classifier towards head classes while reducing the training skills and overhead.
Ranked #1 on
Long-tail Learning
on CIFAR-10-LT (ρ=10)
Efficient Mask Correction for Click-Based Interactive Image Segmentation
To this end, we propose an efficient method to correct the mask with a lightweight mask correction network.
FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation
Inspired by the recent progress on semantic directions on feature-space, we propose to include augmentations in feature space for efficient distillation.
1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking
We extend the classical tracking-by-detection paradigm to this tracking-any-object task.
Ranked #9 on
Multi-Object Tracking
on TAO
(using extra training data)
Correlation-Guided Attention for Corner Detection Based Visual Tracking
Accurate bounding box estimation has recently attracted much attention in the tracking community because traditional multi-scale search strategies cannot estimate tight bounding boxes in many challenging scenarios involving changes to the target.
