International Journal of Computer Vision

The neural radiance field (NeRF) has shown promising results in preserving the fine details of objects and scenes. However, unlike explicit shape representations e.g., mesh, it remains an open problem to build dense correspondences across ...

Pose estimation in crowded scenes is key to understanding human behavior in real-life applications. Most existing CNN-based pose estimation methods often depend on the appearance of visible parts as cues to localize human joints. However, ...

Existing Source-Free Domain Adaptation (SFDA) methods typically adopt the feature distribution alignment paradigm via mining auxiliary information (eg., pseudo-labelling, source domain data generation). However, they are largely limited due to ...

Nowadays, driven by the increasing concern on 3D techniques, resulting in the large-scale 3D data, 3D model classification has attracted enormous attention from both research and industry communities. Most of the current methods highly depend on ...${}^{\mathrm{}}$

Deep neural networks may be susceptible to learning spurious correlations that hold on average but not in atypical test samples. As with the recent emergence of vision transformer (ViT) models, it remains unexplored how spurious correlations are ...

Although conventional matting formulation can separate foreground from background in fractional occupancy which can be caused by highly transparent objects, complex foreground (e.g., net or tree), and objects containing very fine details (e.g., ...

Pre-trained vision transformers have strong representations benefit to various downstream tasks. Recently many parameter-efficient fine-tuning (PEFT) methods have been proposed, and their experiments demonstrate that tuning only 1% extra ...$$

Weakly supervised object localization and semantic segmentation aim to localize objects using only image-level labels. Recently, a new paradigm has emerged by generating a foreground prediction map (FPM) to achieve pixel-level localization. While ...

Discriminating salient moving objects against complex, cluttered backgrounds, with occlusions and challenging environmental conditions like weather and illumination, is essential for stateful scene perception in autonomous systems. We propose a ...

In intelligent transportation systems, parsing traffic signs and transmitting traffic information to humans is an urgent need. However, despite the success achieved in the detection and recognition of low-level circular or triangular traffic signs,...

Neural networks do not generalize well to unseen data with domain shifts—a longstanding problem in machine learning and AI. To overcome the problem, we propose MixStyle, a simple plug-and-play, parameter-free module that can improve domain ...

Domain shift widely exists in the visual world, while modern deep neural networks commonly suffer from severe performance degradation under domain shift due to poor generalization ability, which limits real-world applications. The domain shift ...

Predicting human’s gaze from egocentric videos serves as a critical role for human intention understanding in daily activities. In this paper, we present the first transformer-based model to address the challenging problem of egocentric gaze ...

Single object tracking (SOT) research falls into a cycle—trackers perform well on most benchmarks but quickly fail in challenging scenarios, causing researchers to doubt the insufficient data content and take more effort to construct larger ...

Since real-world training datasets cannot properly sample the long tail of the underlying data distribution, corner cases and rare out-of-domain samples can severely hinder the performance of state-of-the-art models. This problem becomes even more ...

The human visual system has limited capacity in simultaneously processing multiple visual inputs. Consequently, humans rely on shifting their attention from one location to another. When viewing an image of complex scenes, psychology studies and ...

Visual obstacle discovery is a key step towards autonomous navigation of indoor mobile robots. Successful solutions have many applications in multiple scenes. One of the exceptions is the reflective ground. In this case, the reflections on the ...