activity
20212026
most citedInter-Domain Mixup for Semi-Supervised Domain Adaptation

32 citations · 99 across the 77 of their papers we have counts for

collaborators
Showing cs.CVShow all

94 papers · 1 filter

cs.CV2026

SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling

Zheng Liu, Zijian He, Huiguo He +5

Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes, such as objects span differ…

cs.CV2026

MoRoute: Dynamic Routing for In-Context Multimodal Video Generation

Chong Gao, Jie Ma, Zhan Peng +5

Multimodal video generation aims to generate and edit videos conditioned on arbitrary combinations of text, images, and videos within a single model, allowing diverse tasks to shar…

cs.CV2026

AdaAnchor4D: Anchor-Conditioned Spatiotemporal Feature Aggregation for Monocular UAV 4D Reconstruction

Peiyi Xu, Junpeng Zhang, Guanbin Li +6

Monocular UAV videos provide valuable observations for dynamic reconstruction of complex urban scenes. However, such scenes exhibit pronounced spatiotemporal heterogeneity: differe…

cs.CV2026

ARDepth: Auto-regressive Monocular Depth Estimation with Progressive Visual Conditioning

Zijie Wang, Wei Zhang, Weiming Zhang +4

Diffusion models have recently become the dominant paradigm for monocular depth estimation (MDE). However, they implicitly assume that depth can be recovered as a globally smooth f…

cs.CV2026

PhyScene3D: Physically Consistent Interactive 3D Tabletop Scene Generation

Weixing Chen, Zhuoqian Feng, Yang Liu +6

Generating physically consistent 3D tabletop scenes is a fundamental yet underexplored problem for interactive and generalist robotic learning. The challenge stems from dense objec…

cs.CV2026

Non-Forgetting Knowledge Allocation with Bi-level Competition for Class-Incremental Learning

Xiang Tan, Run He, Yawen Cui +6

Class-Incremental Learning (CIL) with pre-trained models (PTMs) aims to sequentially adapt PTMs to new categories without forgetting old knowledge. Built upon PTMs, existing adapte…