Search Results for author:
Found 15 papers, 4 papers with code
MapGPT: Map-Guided Prompting with Adaptive Path Planning for Vision-and-Language Navigation
Embodied agents equipped with GPT as their brains have exhibited extraordinary decision-making and generalization abilities across various tasks.
Divide and Adapt: Active Domain Adaptation via Customized Learning
To accommodate active learning and domain adaption, the two naturally different tasks, in a collaborative framework, we advocate that a customized learning strategy for the target data is the key to the success of ADA solutions.
Exploration and Exploitation of Unlabeled Data for Open-Set Semi-Supervised Learning
In this paper, we address a complex but practical scenario in semi-supervised learning (SSL) named open-set SSL, where unlabeled data contain both in-distribution (ID) and out-of-distribution (OOD) samples.
Towards Accurate Post-Training Quantization for Vision Transformer
We find the main reasons lie in (1) the existing calibration metric is inaccurate in measuring the quantization influence for extremely low-bit representation, and (2) the existing quantization paradigm is unfriendly to the power-law distribution of Softmax.
DRKF: Distilled Rotated Kernel Fusion for Efficient Rotation Invariant Descriptors in Local Feature Matching
The performance of local feature descriptors degrades in the presence of large rotation variations.
Compressing Models with Few Samples: Mimicking then Replacing
Hence, previous methods optimize the compressed model layer-by-layer and try to make every layer have the same outputs as the corresponding layer in the teacher model, which is cumbersome.
Contrastive Attention Network with Dense Field Estimation for Face Completion
This multi-scale architecture is beneficial for the decoder to utilize discriminative representations learned from encoders into images.
Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning
Open-set semi-supervised learning (open-set SSL) investigates a challenging but practical scenario where out-of-distribution (OOD) samples are contained in the unlabeled data.
Rethinking BiSeNet For Real-time Semantic Segmentation
BiSeNet has been proved to be a popular two-stream network for real-time segmentation.
Ranked #8 on
Real-Time Semantic Segmentation
on Cityscapes test
Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition
In this paper, we propose a novel Feature Decomposition and Reconstruction Learning (FDRL) method for effective facial expression recognition.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Query Twice: Dual Mixture Attention Meta Learning for Video Summarization
Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax function.
Ranked #5 on
Supervised Video Summarization
on SumMe
Reference-guided Face Component Editing
Face portrait editing has achieved great progress in recent years.
Grand Challenge of 106-Point Facial Landmark Localization
However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.
