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Found 13 papers, 4 papers with code
Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering
Noisy labels are commonly found in real-world data, which cause performance degradation of deep neural networks.
Video Imprint
In the proposed framework, a dedicated feature alignment module is incorporated for redundancy removal across frames to produce the tensor representation, i. e., the video imprint.
Noise-resistant Deep Metric Learning with Ranking-based Instance Selection
The existence of noisy labels in real-world data negatively impacts the performance of deep learning models.
Intrinsic Temporal Regularization for High-resolution Human Video Synthesis
Temporal consistency is crucial for extending image processing pipelines to the video domain, which is often enforced with flow-based warping error over adjacent frames.
Implicit Subspace Prior Learning for Dual-Blind Face Restoration
Face restoration is an inherently ill-posed problem, where additional prior constraints are typically considered crucial for mitigating such pathology.
Region-adaptive Texture Enhancement for Detailed Person Image Synthesis
The ability to produce convincing textural details is essential for the fidelity of synthesized person images.
Ranked #4 on
Pose Transfer
on Deep-Fashion
Towards Fine-grained Human Pose Transfer with Detail Replenishing Network
Human pose transfer (HPT) is an emerging research topic with huge potential in fashion design, media production, online advertising and virtual reality.
Ladder Loss for Coherent Visual-Semantic Embedding
For visual-semantic embedding, the existing methods normally treat the relevance between queries and candidates in a bipolar way -- relevant or irrelevant, and all "irrelevant" candidates are uniformly pushed away from the query by an equal margin in the embedding space, regardless of their various proximity to the query.
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
For an RNN block, an EleAttG is used for adaptively modulating the input by assigning different levels of importance, i. e., attention, to each element/dimension of the input.
Ranked #3 on
Skeleton Based Action Recognition
on SYSU 3D
Generating Persuasive Visual Storylines for Promotional Videos
Video contents have become a critical tool for promoting products in E-commerce.
Adding Attentiveness to the Neurons in Recurrent Neural Networks
We propose adding a simple yet effective Element-wiseAttention Gate (EleAttG) to an RNN block (e. g., all RNN neurons in a network layer) that empowers the RNN neurons to have the attentiveness capability.
Ranked #98 on
Skeleton Based Action Recognition
on NTU RGB+D
ER3: A Unified Framework for Event Retrieval, Recognition and Recounting
We develop a unified framework for complex event retrieval, recognition and recounting.
Counting Grid Aggregation for Event Retrieval and Recognition
Event retrieval and recognition in a large corpus of videos necessitates a holistic fixed-size visual representation at the video clip level that is comprehensive, compact, and yet discriminative.
