TL;DR
FSG-AID is presented, which integrates fine-grained semantic guidance with an attribute-aware iterative decoder and jointly exploits visual and language features to mine attribute semantics, initialize the target query, and iteratively refine the target representation.
Generalized Visual Grounding (GVG) task aims to localize targets in an image based on referring expressions, extends the classical visual grounding paradigm by integrating multi-target and non-target scenarios. Previous methods typically rely on global semantic matching or coarse-grained region interactions for localiz...
The Visually-Guided Disambiguation Aggregation Aggregation (VGD-Agg) framework is proposed, a framework based on a dual-branch fast-slow architecture that enhances discriminability via two learnable tokens and achieves state-of-the-art results on the proposed benchmarks.
This work formulates active learning for VG under the realistic setting where only raw images are available without accompanying text, and introduces Referred Region Ambiguity, a new acquisition function that measures whether the model's confidence collapses onto a single region or disperses across multiple candidates.
Few-shot segmentation (FSS) aims to segment unseen object categories with a few (e.g., one or five) labeled examples, enabling efficient adaptation to novel classes. Conventional models typically rely on appearance-based visual matching between support and query images for segmentation. While straightforward, these met...
G2D is proposed, a training-free framework that uses a generative VLM to verify CLIP-retrieved candidates against the image and transfers to DCLIP, WaffleCLIP, and CuPL, supporting a practical interface between discriminative proposal and generative visual reasoning.
Camouflaged object detection (COD) aims to segment objects that exhibit high visual similarity to their surroundings, which reduces foreground-background discriminability and weakens boundary evidence across appearance, texture, and structure. Such limitations motivate the use of instruction-conditioned semantics as to...
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