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- Residual Attention Network for Image Classification3,863
The proposed Residual Attention Network is a convolutional neural network using attention mechanism which can incorporate with state-of-art feed forward network architecture in an end-to-end training fashion and can be easily scaled up to hundreds of layers.
- DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection648
The on-going effort of constructing a large- scale benchmark for face forgery detection is presented, with 60, 000 videos constituted by a total of 17.6 million frames, 10 times larger than existing datasets of the same kind.
- Look at Boundary: A Boundary-Aware Face Alignment Algorithm523
A novel boundary-aware face alignment algorithm by utilising boundary lines as the geometric structure of a human face to help facial landmark localisation, which outperforms state-of-the-art methods by a large margin.
- MEAD: A Large-Scale Audio-Visual Dataset for Emotional Talking-Face Generation522
An emotional talking-face generation baseline that enables the manipulation of both emotion and its intensity and could be used for a number of research projects including conditional generation, cross-modal understanding and expression recognition.
- Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation478
A unified and efficient Cross-modality Guided Encoder to not only effectively recalibrate RGB feature responses, but also to distill accurate depth information via multiple stages and aggregate the two recalibrated representations alternatively.
- TAM: Temporal Adaptive Module for Video Recognition388
A new temporal adaptive module (TAM) to generate video-specific temporal kernels based on its own feature map that outperforms other temporal modeling methods consistently, and achieves the state-of-the-art performance under the similar complexity.
- Whole-Body Human Pose Estimation in the Wild376
COCO-WholeBody is introduced which extends COCO dataset with whole-body annotations and is the first benchmark that has manual annotations on the entire human body, including 133 dense landmarks with 68 on the face, 42 on hands and 23 on the body and feet.
- PPDM: Parallel Point Detection and Matching for Real-Time Human-Object Interaction Detection337
A single-stage Human-Object Interaction (HOI) detection method that has outperformed all existing methods on HICO-DET dataset at 37 fps on a single Titan XP GPU is proposed, and is the first real-time HOI detection method.
- SimMatch: Semi-supervised Learning with Similarity Matching271
A new semi-supervised learning framework, SimMatch, is introduced, which simulta-neously considers semantic similarity and instance similarity and the unfolding and aggregation operation which allows these two similarities be isomorphically transformed with each other is proposed.
- A Real-Time Cross-Modality Correlation Filtering Method for Referring Expression Comprehension253
A novel Realtime Cross-modality Correlation Filtering method (RCCF) that reformulates the referring expression comprehension as a correlation ï¬ltering process and achieves leading performance in RefClef, RefCOCO, Ref COCO+ and RefC OCOg benchmarks.
- ReenactGAN: Learning to Reenact Faces via Boundary Transfer229
The proposed method, known as ReenactGAN, is capable of transferring facial movements and expressions from an arbitrary person's monocular video input to a target person’s video, and can perform photo-realistic face reenactment.
- A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation219
A coarse-to-fine strategy which estimates a basic gaze direction from face image and refines it with corresponding residual predicted from eye images, and a framework which introduces a bi-gram model to bridge gaze residual andbasic gaze direction, and an attention component to adaptively acquire suitable fine-grained feature are proposed.
- The Devil of Face Recognition Is in the Noise217
This work contributes cleaned subsets of popular face databases, i.e., MegaFace and MS-Celeb-1M datasets, and builds a new large-scale noise-controlled IMDb-Face dataset, and investigates ways to improve data cleanliness, including a comprehensive user study on the influence of data labeling strategies to annotation accuracy.
- Deep Comprehensive Correlation Mining for Image Clustering204
A novel clustering framework, named deep comprehensive correlation mining~(DCCM), for exploring and taking full advantage of various kinds of correlations behind the unlabeled data from three aspects: Instead of only using pair-wise information, pseudo-label supervision is proposed to investigate category information and learn discriminative features.
- CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection193
This paper proposes CentripetalNet which uses centripetals shift to pair corner keypoints from the same instance and predicts the position and the centripeteal shift of the corner points and matches corners whose shifted results are aligned.
- Not All Tokens Are Equal: Human-centric Visual Analysis via Token Clustering Transformer192
A novel Vision Transformer, called Token Clustering Transformer (TCFormer), which merges tokens by progressive clustering, where the tokens can be merged from different locations with flexible shapes and sizes, which is beneficial to capturing detailed information.
- A Keypoint-based Global Association Network for Lane Detection191
A Global Association Network (GANet) is proposed to formulate the lane detection problem from a new perspective, where each keypoint is directly regressed to the starting point of the lane line instead of point-by-point extension, which outperforms previous methods.
- Reformulating HOI Detection as Adaptive Set Prediction190
This paper reformulate HOI detection as an adaptive set prediction problem, with this novel formulation, it is proposed an Adaptive Set-based one-stage framework (AS-Net) with parallel instance and interaction branches and an effective instance-aware attention module.
- Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow187
The approach, namely Diffusion-based Conditional Inpainting for Virtual Try-ON(DCI-VTON), effectively utilizes the power of the diffusion model, and the incorporation of the warping module helps to produce high-quality and realistic virtual try-on results.
- Everybody’s Talkin’: Let Me Talk as You Want172
A method to edit a target portrait footage by taking a sequence of audio as input to synthesize a photo-realistic video, which is end-to-end learnable and robust to voice variations in the source audio.
- Weakly Supervised Contrastive Learning168
A weakly supervised contrastive learning framework (WCL) based on two projection heads, one of which will perform the regular instance discrimination task, and the other head will use a graph-based method to explore similar samples and generate a weak label to pull the similar images closer.
- GreedyNAS: Towards Fast One-Shot NAS With Greedy Supernet159
This paper proposes a multi-path sampling strategy with rejection, and greedily filter the weak paths to ease the burden of supernet by encouraging it to focus more on evaluation of those potentially-good ones, which are identified using a surrogate portion of validation data.
- Differentiable Hierarchical Graph Grouping for Multi-person Pose Estimation147
This paper proposes a novel differentiable Hierarchical Graph Grouping (HGG) method, which takes human keypoint candidates as graph nodes and clusters keypoints in a multi-layer graph neural network model and improves the performance of bottom-up pose estimation methods.
- Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space144
This paper examines the diversity of teacher models in the gradient space and regard the ensemble knowledge distillation as a multi-objective optimization problem so that the method can be seen as a dynamic weighting method for each teacher in the ensemble.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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